Warning: Permanently added '3.237.9.254' (ED25519) to the list of known hosts. You can reproduce this build on your computer by running: sudo dnf install copr-rpmbuild /usr/bin/copr-rpmbuild --verbose --drop-resultdir --task-url https://copr.fedorainfracloud.org/backend/get-build-task/7480677-fedora-rawhide-x86_64 --chroot fedora-rawhide-x86_64 Version: 0.73 PID: 13518 Logging PID: 13519 Task: {'allow_user_ssh': False, 'appstream': False, 'background': False, 'bootstrap': 'off', 'build_id': 7480677, 'buildroot_pkgs': [], 'chroot': 'fedora-rawhide-x86_64', 'enable_net': False, 'fedora_review': False, 'git_hash': 'f25f305dda7edfb291d2a34f83c4c720a71f126b', 'git_repo': 'https://copr-dist-git.fedorainfracloud.org/git/iucar/cran/R-CRAN-RBesT', 'isolation': 'default', 'memory_reqs': 2048, 'package_name': 'R-CRAN-RBesT', 'package_version': '1.7.3-1.copr7480677', 'project_dirname': 'cran', 'project_name': 'cran', 'project_owner': 'iucar', 'repo_priority': None, 'repos': [{'baseurl': 'https://download.copr.fedorainfracloud.org/results/iucar/cran/fedora-rawhide-x86_64/', 'id': 'copr_base', 'name': 'Copr repository', 'priority': None}], 'sandbox': 'iucar/cran--iucar', 'source_json': {}, 'source_type': None, 'ssh_public_keys': None, 'submitter': 'iucar', 'tags': [], 'task_id': '7480677-fedora-rawhide-x86_64', 'timeout': None, 'uses_devel_repo': False, 'with_opts': [], 'without_opts': []} Running: git clone https://copr-dist-git.fedorainfracloud.org/git/iucar/cran/R-CRAN-RBesT /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT --depth 500 --no-single-branch --recursive cmd: ['git', 'clone', 'https://copr-dist-git.fedorainfracloud.org/git/iucar/cran/R-CRAN-RBesT', '/var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT', '--depth', '500', '--no-single-branch', '--recursive'] cwd: . rc: 0 stdout: stderr: Cloning into '/var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT'... Running: git checkout f25f305dda7edfb291d2a34f83c4c720a71f126b -- cmd: ['git', 'checkout', 'f25f305dda7edfb291d2a34f83c4c720a71f126b', '--'] cwd: /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT rc: 0 stdout: stderr: Note: switching to 'f25f305dda7edfb291d2a34f83c4c720a71f126b'. You are in 'detached HEAD' state. You can look around, make experimental changes and commit them, and you can discard any commits you make in this state without impacting any branches by switching back to a branch. If you want to create a new branch to retain commits you create, you may do so (now or later) by using -c with the switch command. Example: git switch -c Or undo this operation with: git switch - Turn off this advice by setting config variable advice.detachedHead to false HEAD is now at f25f305 automatic import of R-CRAN-RBesT Running: copr-distgit-client sources cmd: ['copr-distgit-client', 'sources'] cwd: /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT rc: 0 stdout: stderr: INFO: Reading stdout from command: git rev-parse --abbrev-ref HEAD INFO: Reading stdout from command: git rev-parse HEAD INFO: Reading sources specification file: sources INFO: Downloading RBesT_1.7-3.tar.gz INFO: Reading stdout from command: curl --help all INFO: Calling: curl -H Pragma: -o RBesT_1.7-3.tar.gz --location --connect-timeout 60 --retry 3 --retry-delay 10 --remote-time --show-error --fail --retry-all-errors https://copr-dist-git.fedorainfracloud.org/repo/pkgs/iucar/cran/R-CRAN-RBesT/RBesT_1.7-3.tar.gz/md5/a69c6d551c836ca4cb990793157aacf5/RBesT_1.7-3.tar.gz % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 741k 100 741k 0 0 14.0M 0 --:--:-- --:--:-- --:--:-- 14.1M INFO: Reading stdout from command: md5sum RBesT_1.7-3.tar.gz /usr/bin/tail: /var/lib/copr-rpmbuild/main.log: file truncated Running (timeout=None): unbuffer mock --spec /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT/R-CRAN-RBesT.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1716467991.378440 -r /var/lib/copr-rpmbuild/results/configs/child.cfg INFO: mock.py version 5.5 starting (python version = 3.12.1, NVR = mock-5.5-1.fc39), args: /usr/libexec/mock/mock --spec /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT/R-CRAN-RBesT.spec --sources /var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT --resultdir /var/lib/copr-rpmbuild/results --uniqueext 1716467991.378440 -r /var/lib/copr-rpmbuild/results/configs/child.cfg Start: init plugins INFO: tmpfs initialized INFO: selinux enabled INFO: chroot_scan: initialized INFO: compress_logs: initialized Finish: init plugins INFO: Signal handler active Start: run INFO: Start(/var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT/R-CRAN-RBesT.spec) Config(fedora-rawhide-x86_64) Start: clean chroot Finish: clean chroot Mock Version: 5.5 INFO: Mock Version: 5.5 Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-rawhide-x86_64-1716467991.378440/root. INFO: calling preinit hooks INFO: enabled root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Package manager dnf5 detected and used (fallback) INFO: Buildroot is handled by package management from host and used with --installroot: rpm-4.19.1.1-1.fc39.x86_64 rpm-sequoia-1.6.0-1.fc39.x86_64 python3-dnf-4.19.2-1.fc39.noarch python3-dnf-plugins-core-4.6.0-1.fc39.noarch yum-4.19.2-1.fc39.noarch dnf5-5.1.17-1.fc39.x86_64 dnf5-plugins-5.1.17-1.fc39.x86_64 Start: installing minimal buildroot with dnf5 Updating and loading repositories: fedora 100% | 37.3 MiB/s | 21.0 MiB | 00m01s Copr repository 100% | 113.6 MiB/s | 11.8 MiB | 00m00s Repositories loaded. Package Arch Version Repository Size Installing group/module packages: bash x86_64 5.2.26-3.fc40 fedora 8.1 MiB bzip2 x86_64 1.0.8-18.fc40 fedora 91.7 KiB coreutils x86_64 9.5-1.fc41 fedora 5.5 MiB cpio x86_64 2.15-1.fc40 fedora 1.1 MiB diffutils x86_64 3.10-5.fc40 fedora 1.6 MiB fedora-release-common noarch 41-0.10 fedora 19.2 KiB findutils x86_64 1:4.9.0-8.fc40 fedora 1.5 MiB gawk x86_64 5.3.0-3.fc40 fedora 1.7 MiB glibc-minimal-langpack x86_64 2.39.9000-18.fc41 fedora 0.0 B grep x86_64 3.11-8.fc41 fedora 1.0 MiB gzip x86_64 1.13-1.fc40 fedora 385.0 KiB info x86_64 7.1-2.fc40 fedora 357.8 KiB patch x86_64 2.7.6-24.fc40 fedora 262.8 KiB redhat-rpm-config noarch 290-1.fc41 fedora 183.6 KiB rpm-build x86_64 4.19.1.1-2.fc41 fedora 173.7 KiB sed x86_64 4.9-1.fc40 fedora 861.5 KiB shadow-utils x86_64 2:4.15.1-5.fc41 fedora 4.1 MiB tar x86_64 2:1.35-3.fc40 fedora 2.9 MiB unzip x86_64 6.0-63.fc40 fedora 382.8 KiB util-linux x86_64 2.40.1-1.fc41 fedora 3.7 MiB which x86_64 2.21-41.fc40 fedora 80.2 KiB xz x86_64 1:5.4.6-3.fc41 fedora 2.0 MiB Installing dependencies: add-determinism-nopython x86_64 0.2.0-8.fc41 fedora 2.5 MiB alternatives x86_64 1.27-1.fc41 fedora 66.3 KiB ansible-srpm-macros noarch 1-15.fc41 fedora 35.7 KiB audit-libs x86_64 4.0.1-2.fc41 fedora 327.3 KiB authselect x86_64 1.5.0-5.fc41 fedora 153.6 KiB authselect-libs x86_64 1.5.0-5.fc41 fedora 818.2 KiB basesystem noarch 11-20.fc40 fedora 0.0 B binutils x86_64 2.42.50-11.fc41 fedora 27.5 MiB binutils-gold x86_64 2.42.50-11.fc41 fedora 2.0 MiB build-reproducibility-srpm-macros noarch 0.2.0-8.fc41 fedora 769.0 B bzip2-libs x86_64 1.0.8-18.fc40 fedora 80.7 KiB ca-certificates noarch 2023.2.62_v7.0.401-6.fc40 fedora 2.3 MiB coreutils-common x86_64 9.5-1.fc41 fedora 11.2 MiB cracklib x86_64 2.9.11-5.fc40 fedora 238.9 KiB crypto-policies noarch 20240521-1.gitf71d135.fc41 fedora 120.0 KiB curl x86_64 8.8.0-1.fc41 fedora 743.7 KiB cyrus-sasl-lib x86_64 2.1.28-22.fc41 fedora 2.3 MiB debugedit x86_64 5.0-16.fc41 fedora 199.3 KiB dwz x86_64 0.15-6.fc40 fedora 290.9 KiB ed x86_64 1.20.2-1.fc41 fedora 146.8 KiB efi-srpm-macros noarch 5-11.fc40 fedora 40.1 KiB elfutils x86_64 0.191-7.fc41 fedora 2.5 MiB elfutils-debuginfod-client x86_64 0.191-7.fc41 fedora 64.9 KiB elfutils-default-yama-scope noarch 0.191-7.fc41 fedora 1.8 KiB elfutils-libelf x86_64 0.191-7.fc41 fedora 1.2 MiB elfutils-libs x86_64 0.191-7.fc41 fedora 646.1 KiB fedora-gpg-keys noarch 41-0.2 fedora 124.7 KiB fedora-release noarch 41-0.10 fedora 0.0 B fedora-release-identity-basic noarch 41-0.10 fedora 694.0 B fedora-repos noarch 41-0.2 fedora 4.9 KiB fedora-repos-rawhide noarch 41-0.2 fedora 2.2 KiB file x86_64 5.45-5.fc41 fedora 103.5 KiB file-libs x86_64 5.45-5.fc41 fedora 9.9 MiB filesystem x86_64 3.18-9.fc41 fedora 106.0 B fonts-srpm-macros noarch 1:2.0.5-14.fc40 fedora 55.3 KiB forge-srpm-macros noarch 0.3.1-1.fc41 fedora 39.0 KiB fpc-srpm-macros noarch 1.3-12.fc40 fedora 144.0 B gdb-minimal x86_64 14.2-7.fc41 fedora 12.7 MiB gdbm x86_64 1:1.23-6.fc40 fedora 460.9 KiB gdbm-libs x86_64 1:1.23-6.fc40 fedora 121.9 KiB ghc-srpm-macros noarch 1.9.1-1.fc41 fedora 747.0 B glibc x86_64 2.39.9000-18.fc41 fedora 6.7 MiB glibc-common x86_64 2.39.9000-18.fc41 fedora 1.0 MiB glibc-gconv-extra x86_64 2.39.9000-18.fc41 fedora 7.8 MiB gmp x86_64 1:6.3.0-1.fc41 fedora 803.4 KiB gnat-srpm-macros noarch 6-5.fc40 fedora 1.0 KiB go-srpm-macros noarch 3.6.0-1.fc41 fedora 60.8 KiB jansson x86_64 2.13.1-9.fc40 fedora 88.3 KiB kernel-srpm-macros noarch 1.0-23.fc41 fedora 1.9 KiB keyutils-libs x86_64 1.6.3-3.fc40 fedora 54.4 KiB krb5-libs x86_64 1.21.2-5.fc40 fedora 2.3 MiB libacl x86_64 2.3.2-1.fc40 fedora 40.0 KiB libarchive x86_64 3.7.4-1.fc41 fedora 914.6 KiB libattr x86_64 2.5.2-3.fc40 fedora 28.5 KiB libblkid x86_64 2.40.1-1.fc41 fedora 258.5 KiB libbrotli x86_64 1.1.0-3.fc40 fedora 829.5 KiB libcap x86_64 2.70-1.fc41 fedora 220.3 KiB libcap-ng x86_64 0.8.5-1.fc41 fedora 69.1 KiB libcom_err x86_64 1.47.0-5.fc40 fedora 67.2 KiB libcurl x86_64 8.8.0-1.fc41 fedora 805.7 KiB libeconf x86_64 0.6.2-1.fc41 fedora 58.0 KiB libevent x86_64 2.1.12-13.fc41 fedora 895.6 KiB libfdisk x86_64 2.40.1-1.fc41 fedora 362.9 KiB libffi x86_64 3.4.6-1.fc41 fedora 82.4 KiB libgcc x86_64 14.1.1-1.fc41 fedora 270.6 KiB libgomp x86_64 14.1.1-1.fc41 fedora 519.5 KiB libidn2 x86_64 2.3.7-1.fc40 fedora 329.1 KiB libmount x86_64 2.40.1-1.fc41 fedora 351.8 KiB libnghttp2 x86_64 1.62.0-1.fc41 fedora 166.1 KiB libnsl2 x86_64 2.0.1-1.fc40 fedora 57.9 KiB libpkgconf x86_64 2.1.1-1.fc41 fedora 74.2 KiB libpsl x86_64 0.21.5-3.fc40 fedora 80.5 KiB libpwquality x86_64 1.4.5-9.fc40 fedora 417.8 KiB libselinux x86_64 3.6-4.fc40 fedora 173.0 KiB libsemanage x86_64 3.6-3.fc40 fedora 293.5 KiB libsepol x86_64 3.6-3.fc40 fedora 802.0 KiB libsmartcols x86_64 2.40.1-1.fc41 fedora 180.4 KiB libssh x86_64 0.10.6-6.fc41 fedora 513.3 KiB libssh-config noarch 0.10.6-6.fc41 fedora 277.0 B libstdc++ x86_64 14.1.1-1.fc41 fedora 2.8 MiB libtasn1 x86_64 4.19.0-6.fc40 fedora 175.7 KiB libtirpc x86_64 1.3.4-1.rc3.fc41 fedora 202.8 KiB libtool-ltdl x86_64 2.4.7-10.fc40 fedora 66.2 KiB libunistring x86_64 1.1-7.fc41 fedora 1.7 MiB libutempter x86_64 1.2.1-13.fc40 fedora 57.7 KiB libuuid x86_64 2.40.1-1.fc41 fedora 37.4 KiB libverto x86_64 0.3.2-8.fc40 fedora 29.5 KiB libxcrypt x86_64 4.4.36-5.fc40 fedora 262.8 KiB libxml2 x86_64 2.12.7-1.fc41 fedora 1.7 MiB libzstd x86_64 1.5.6-1.fc41 fedora 787.9 KiB lua-libs x86_64 5.4.6-5.fc40 fedora 281.1 KiB lua-srpm-macros noarch 1-13.fc40 fedora 1.3 KiB lz4-libs x86_64 1.9.4-6.fc40 fedora 129.4 KiB mpfr x86_64 4.2.1-4.fc41 fedora 828.0 KiB ncurses-base noarch 6.4-12.20240127.fc40 fedora 326.2 KiB ncurses-libs x86_64 6.4-12.20240127.fc40 fedora 963.2 KiB ocaml-srpm-macros noarch 9-3.fc40 fedora 1.9 KiB openblas-srpm-macros noarch 2-17.fc41 fedora 112.0 B openldap x86_64 2.6.7-1.fc40 fedora 635.1 KiB openssl-libs x86_64 1:3.2.1-6.fc41 fedora 7.8 MiB p11-kit x86_64 0.25.3-4.fc40 fedora 2.2 MiB p11-kit-trust x86_64 0.25.3-4.fc40 fedora 391.4 KiB package-notes-srpm-macros noarch 0.5-11.fc40 fedora 1.6 KiB pam x86_64 1.6.1-1.fc41 fedora 1.8 MiB pam-libs x86_64 1.6.1-1.fc41 fedora 135.0 KiB pcre2 x86_64 10.43-2.fc41.1 fedora 653.5 KiB pcre2-syntax noarch 10.43-2.fc41.1 fedora 249.0 KiB perl-srpm-macros noarch 1-53.fc40 fedora 861.0 B pkgconf x86_64 2.1.1-1.fc41 fedora 82.9 KiB pkgconf-m4 noarch 2.1.1-1.fc41 fedora 13.9 KiB pkgconf-pkg-config x86_64 2.1.1-1.fc41 fedora 989.0 B popt x86_64 1.19-6.fc40 fedora 136.9 KiB publicsuffix-list-dafsa noarch 20240107-3.fc40 fedora 67.5 KiB pyproject-srpm-macros noarch 1.12.0-1.fc40 fedora 1.5 KiB python-srpm-macros noarch 3.12-9.fc41 fedora 50.5 KiB qt5-srpm-macros noarch 5.15.13-1.fc41 fedora 492.0 B qt6-srpm-macros noarch 6.7.0-1.fc41 fedora 456.0 B readline x86_64 8.2-8.fc40 fedora 489.2 KiB rpm x86_64 4.19.1.1-2.fc41 fedora 3.0 MiB rpm-build-libs x86_64 4.19.1.1-2.fc41 fedora 198.4 KiB rpm-libs x86_64 4.19.1.1-2.fc41 fedora 709.9 KiB rpm-sequoia x86_64 1.6.0-2.fc40 fedora 2.2 MiB rust-srpm-macros noarch 26.3-1.fc41 fedora 4.8 KiB setup noarch 2.14.5-2.fc40 fedora 720.4 KiB sqlite-libs x86_64 3.45.3-1.fc41 fedora 1.4 MiB systemd-libs x86_64 256~rc2-1.fc41 fedora 2.0 MiB util-linux-core x86_64 2.40.1-1.fc41 fedora 1.5 MiB xxhash-libs x86_64 0.8.2-2.fc40 fedora 88.5 KiB xz-libs x86_64 1:5.4.6-3.fc41 fedora 209.8 KiB zig-srpm-macros noarch 1-2.fc40 fedora 1.1 KiB zip x86_64 3.0-40.fc40 fedora 703.2 KiB zlib-ng-compat x86_64 2.1.6-3.fc41 fedora 134.0 KiB zstd x86_64 1.5.6-1.fc41 fedora 1.7 MiB Installing groups: Buildsystem building group Transaction Summary: Installing: 155 packages Total size of inbound packages is 54 MiB. Need to download 54 MiB. After this operation 181 MiB will be used (install 181 MiB, remove 0 B). [ 1/155] bzip2-0:1.0.8-18.fc40.x86_64 100% | 3.7 MiB/s | 52.4 KiB | 00m00s [ 2/155] cpio-0:2.15-1.fc40.x86_64 100% | 71.3 MiB/s | 292.2 KiB | 00m00s [ 3/155] bash-0:5.2.26-3.fc40.x86_64 100% | 86.0 MiB/s | 1.8 MiB | 00m00s [ 4/155] coreutils-0:9.5-1.fc41.x86_64 100% | 47.7 MiB/s | 1.1 MiB | 00m00s [ 5/155] diffutils-0:3.10-5.fc40.x86_6 100% | 99.0 MiB/s | 405.5 KiB | 00m00s [ 6/155] fedora-release-common-0:41-0. 100% | 7.1 MiB/s | 21.9 KiB | 00m00s [ 7/155] glibc-minimal-langpack-0:2.39 100% | 54.5 MiB/s | 111.6 KiB | 00m00s [ 8/155] findutils-1:4.9.0-8.fc40.x86_ 100% | 96.1 MiB/s | 491.9 KiB | 00m00s [ 9/155] grep-0:3.11-8.fc41.x86_64 100% | 97.4 MiB/s | 299.3 KiB | 00m00s [ 10/155] info-0:7.1-2.fc40.x86_64 100% | 89.0 MiB/s | 182.3 KiB | 00m00s [ 11/155] gzip-0:1.13-1.fc40.x86_64 100% | 33.3 MiB/s | 170.6 KiB | 00m00s [ 12/155] patch-0:2.7.6-24.fc40.x86_64 100% | 31.9 MiB/s | 130.7 KiB | 00m00s [ 13/155] sed-0:4.9-1.fc40.x86_64 100% | 77.7 MiB/s | 318.2 KiB | 00m00s [ 14/155] redhat-rpm-config-0:290-1.fc4 100% | 13.4 MiB/s | 82.3 KiB | 00m00s [ 15/155] rpm-build-0:4.19.1.1-2.fc41.x 100% | 10.7 MiB/s | 76.7 KiB | 00m00s [ 16/155] unzip-0:6.0-63.fc40.x86_64 100% | 45.1 MiB/s | 184.5 KiB | 00m00s [ 17/155] tar-2:1.35-3.fc40.x86_64 100% | 119.5 MiB/s | 856.6 KiB | 00m00s [ 18/155] shadow-utils-2:4.15.1-5.fc41. 100% | 131.9 MiB/s | 1.3 MiB | 00m00s [ 19/155] which-0:2.21-41.fc40.x86_64 100% | 10.1 MiB/s | 41.4 KiB | 00m00s [ 20/155] xz-1:5.4.6-3.fc41.x86_64 100% | 90.7 MiB/s | 557.5 KiB | 00m00s [ 21/155] filesystem-0:3.18-9.fc41.x86_ 100% | 181.1 MiB/s | 1.1 MiB | 00m00s [ 22/155] util-linux-0:2.40.1-1.fc41.x8 100% | 109.3 MiB/s | 1.2 MiB | 00m00s [ 23/155] glibc-0:2.39.9000-18.fc41.x86 100% | 224.6 MiB/s | 2.2 MiB | 00m00s [ 24/155] ncurses-libs-0:6.4-12.2024012 100% | 36.1 MiB/s | 332.5 KiB | 00m00s [ 25/155] bzip2-libs-0:1.0.8-18.fc40.x8 100% | 20.0 MiB/s | 40.9 KiB | 00m00s [ 26/155] coreutils-common-0:9.5-1.fc41 100% | 303.1 MiB/s | 2.1 MiB | 00m00s [ 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libevent-0:2.1.12-13.fc41.x86 100% | 50.2 MiB/s | 257.2 KiB | 00m00s -------------------------------------------------------------------------------- [155/155] Total 100% | 150.6 MiB/s | 53.8 MiB | 00m00s Running transaction Importing PGP key 0xE99D6AD1: Userid : "Fedora (41) " Fingerprint: 466CF2D8B60BC3057AA9453ED0622462E99D6AD1 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-41-primary The key was successfully imported. Importing PGP key 0xE99D6AD1: Userid : "Fedora (41) " Fingerprint: 466CF2D8B60BC3057AA9453ED0622462E99D6AD1 From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-41-primary The key was successfully imported. Importing PGP key 0xA15B79CC: Userid : "Fedora (40) " Fingerprint: 115DF9AEF857853EE8445D0A0727707EA15B79CC From : file:///usr/share/distribution-gpg-keys/fedora/RPM-GPG-KEY-fedora-40-primary The key was successfully imported. [ 1/157] Verify package files 100% | 756.0 B/s | 155.0 B | 00m00s >>> Running pre-transaction scriptlet: filesystem-0:3.18-9.fc41.x86_64 >>> Stop pre-transaction scriptlet: filesystem-0:3.18-9.fc41.x86_64 [ 2/157] Prepare transaction 100% | 4.3 KiB/s | 155.0 B | 00m00s [ 3/157] Installing libgcc-0:14.1.1-1. 100% | 133.0 MiB/s | 272.3 KiB | 00m00s >>> Running post-install scriptlet: libgcc-0:14.1.1-1.fc41.x86_64 >>> Stop post-install scriptlet: libgcc-0:14.1.1-1.fc41.x86_64 [ 4/157] Installing crypto-policies-0: 100% | 35.9 MiB/s | 147.0 KiB | 00m00s >>> Running post-install scriptlet: crypto-policies-0:20240521-1.gitf71d135.fc41 >>> Stop post-install scriptlet: crypto-policies-0:20240521-1.gitf71d135.fc41.no [ 5/157] Installing fedora-release-ide 100% | 0.0 B/s | 952.0 B | 00m00s [ 6/157] Installing fedora-repos-rawhi 100% | 0.0 B/s | 2.4 KiB | 00m00s [ 7/157] Installing fedora-gpg-keys-0: 100% | 55.2 MiB/s | 169.7 KiB | 00m00s [ 8/157] Installing fedora-repos-0:41- 100% | 0.0 B/s | 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Installing ncurses-libs-0:6.4 100% | 236.7 MiB/s | 969.7 KiB | 00m00s >>> Running pre-install scriptlet: glibc-0:2.39.9000-18.fc41.x86_64 >>> Stop pre-install scriptlet: glibc-0:2.39.9000-18.fc41.x86_64 [ 21/157] Installing glibc-0:2.39.9000- 100% | 231.7 MiB/s | 6.7 MiB | 00m00s >>> Running post-install scriptlet: glibc-0:2.39.9000-18.fc41.x86_64 >>> Stop post-install scriptlet: glibc-0:2.39.9000-18.fc41.x86_64 [ 22/157] Installing bash-0:5.2.26-3.fc 100% | 429.5 MiB/s | 8.2 MiB | 00m00s >>> Running post-install scriptlet: bash-0:5.2.26-3.fc40.x86_64 >>> Stop post-install scriptlet: bash-0:5.2.26-3.fc40.x86_64 [ 23/157] Installing glibc-common-0:2.3 100% | 205.5 MiB/s | 1.0 MiB | 00m00s [ 24/157] Installing glibc-gconv-extra- 100% | 262.1 MiB/s | 7.9 MiB | 00m00s >>> Running post-install scriptlet: glibc-gconv-extra-0:2.39.9000-18.fc41.x86_64 >>> Stop post-install scriptlet: glibc-gconv-extra-0:2.39.9000-18.fc41.x86_64 [ 25/157] Installing zlib-ng-compat-0:2 100% | 131.6 MiB/s | 134.8 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[151/157] Installing python-srpm-macros 100% | 0.0 B/s | 51.7 KiB | 00m00s [152/157] Installing redhat-rpm-config- 100% | 92.8 MiB/s | 190.1 KiB | 00m00s [153/157] Installing rpm-build-0:4.19.1 100% | 88.8 MiB/s | 181.9 KiB | 00m00s [154/157] Installing pyproject-srpm-mac 100% | 2.0 MiB/s | 2.1 KiB | 00m00s [155/157] Installing util-linux-0:2.40. 100% | 178.3 MiB/s | 3.7 MiB | 00m00s >>> Running post-install scriptlet: util-linux-0:2.40.1-1.fc41.x86_64 >>> Stop post-install scriptlet: util-linux-0:2.40.1-1.fc41.x86_64 [156/157] Installing which-0:2.21-41.fc 100% | 80.5 MiB/s | 82.4 KiB | 00m00s [157/157] Installing info-0:7.1-2.fc40. 100% | 449.4 KiB/s | 358.2 KiB | 00m01s >>> Running post-transaction scriptlet: filesystem-0:3.18-9.fc41.x86_64 >>> Stop post-transaction scriptlet: filesystem-0:3.18-9.fc41.x86_64 >>> Running post-transaction scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.f >>> Stop post-transaction scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.fc40 >>> Running post-transaction scriptlet: authselect-libs-0:1.5.0-5.fc41.x86_64 >>> Stop post-transaction scriptlet: authselect-libs-0:1.5.0-5.fc41.x86_64 >>> Running post-transaction scriptlet: rpm-0:4.19.1.1-2.fc41.x86_64 >>> Stop post-transaction scriptlet: rpm-0:4.19.1.1-2.fc41.x86_64 >>> Running trigger-install scriptlet: glibc-common-0:2.39.9000-18.fc41.x86_64 >>> Stop trigger-install scriptlet: glibc-common-0:2.39.9000-18.fc41.x86_64 >>> Running trigger-install scriptlet: info-0:7.1-2.fc40.x86_64 >>> Stop trigger-install scriptlet: info-0:7.1-2.fc40.x86_64 Finish: installing minimal buildroot with dnf5 Start: creating root cache Finish: creating root cache Finish: chroot init INFO: Installed packages: INFO: add-determinism-nopython-0.2.0-8.fc41.x86_64 alternatives-1.27-1.fc41.x86_64 ansible-srpm-macros-1-15.fc41.noarch audit-libs-4.0.1-2.fc41.x86_64 authselect-1.5.0-5.fc41.x86_64 authselect-libs-1.5.0-5.fc41.x86_64 basesystem-11-20.fc40.noarch bash-5.2.26-3.fc40.x86_64 binutils-2.42.50-11.fc41.x86_64 binutils-gold-2.42.50-11.fc41.x86_64 build-reproducibility-srpm-macros-0.2.0-8.fc41.noarch bzip2-1.0.8-18.fc40.x86_64 bzip2-libs-1.0.8-18.fc40.x86_64 ca-certificates-2023.2.62_v7.0.401-6.fc40.noarch coreutils-9.5-1.fc41.x86_64 coreutils-common-9.5-1.fc41.x86_64 cpio-2.15-1.fc40.x86_64 cracklib-2.9.11-5.fc40.x86_64 crypto-policies-20240521-1.gitf71d135.fc41.noarch curl-8.8.0-1.fc41.x86_64 cyrus-sasl-lib-2.1.28-22.fc41.x86_64 debugedit-5.0-16.fc41.x86_64 diffutils-3.10-5.fc40.x86_64 dwz-0.15-6.fc40.x86_64 ed-1.20.2-1.fc41.x86_64 efi-srpm-macros-5-11.fc40.noarch elfutils-0.191-7.fc41.x86_64 elfutils-debuginfod-client-0.191-7.fc41.x86_64 elfutils-default-yama-scope-0.191-7.fc41.noarch elfutils-libelf-0.191-7.fc41.x86_64 elfutils-libs-0.191-7.fc41.x86_64 fedora-gpg-keys-41-0.2.noarch fedora-release-41-0.10.noarch fedora-release-common-41-0.10.noarch fedora-release-identity-basic-41-0.10.noarch fedora-repos-41-0.2.noarch fedora-repos-rawhide-41-0.2.noarch file-5.45-5.fc41.x86_64 file-libs-5.45-5.fc41.x86_64 filesystem-3.18-9.fc41.x86_64 findutils-4.9.0-8.fc40.x86_64 fonts-srpm-macros-2.0.5-14.fc40.noarch forge-srpm-macros-0.3.1-1.fc41.noarch fpc-srpm-macros-1.3-12.fc40.noarch gawk-5.3.0-3.fc40.x86_64 gdb-minimal-14.2-7.fc41.x86_64 gdbm-1.23-6.fc40.x86_64 gdbm-libs-1.23-6.fc40.x86_64 ghc-srpm-macros-1.9.1-1.fc41.noarch glibc-2.39.9000-18.fc41.x86_64 glibc-common-2.39.9000-18.fc41.x86_64 glibc-gconv-extra-2.39.9000-18.fc41.x86_64 glibc-minimal-langpack-2.39.9000-18.fc41.x86_64 gmp-6.3.0-1.fc41.x86_64 gnat-srpm-macros-6-5.fc40.noarch go-srpm-macros-3.6.0-1.fc41.noarch gpg-pubkey-a15b79cc-63d04c2c gpg-pubkey-e99d6ad1-64d2612c grep-3.11-8.fc41.x86_64 gzip-1.13-1.fc40.x86_64 info-7.1-2.fc40.x86_64 jansson-2.13.1-9.fc40.x86_64 kernel-srpm-macros-1.0-23.fc41.noarch keyutils-libs-1.6.3-3.fc40.x86_64 krb5-libs-1.21.2-5.fc40.x86_64 libacl-2.3.2-1.fc40.x86_64 libarchive-3.7.4-1.fc41.x86_64 libattr-2.5.2-3.fc40.x86_64 libblkid-2.40.1-1.fc41.x86_64 libbrotli-1.1.0-3.fc40.x86_64 libcap-2.70-1.fc41.x86_64 libcap-ng-0.8.5-1.fc41.x86_64 libcom_err-1.47.0-5.fc40.x86_64 libcurl-8.8.0-1.fc41.x86_64 libeconf-0.6.2-1.fc41.x86_64 libevent-2.1.12-13.fc41.x86_64 libfdisk-2.40.1-1.fc41.x86_64 libffi-3.4.6-1.fc41.x86_64 libgcc-14.1.1-1.fc41.x86_64 libgomp-14.1.1-1.fc41.x86_64 libidn2-2.3.7-1.fc40.x86_64 libmount-2.40.1-1.fc41.x86_64 libnghttp2-1.62.0-1.fc41.x86_64 libnsl2-2.0.1-1.fc40.x86_64 libpkgconf-2.1.1-1.fc41.x86_64 libpsl-0.21.5-3.fc40.x86_64 libpwquality-1.4.5-9.fc40.x86_64 libselinux-3.6-4.fc40.x86_64 libsemanage-3.6-3.fc40.x86_64 libsepol-3.6-3.fc40.x86_64 libsmartcols-2.40.1-1.fc41.x86_64 libssh-0.10.6-6.fc41.x86_64 libssh-config-0.10.6-6.fc41.noarch libstdc++-14.1.1-1.fc41.x86_64 libtasn1-4.19.0-6.fc40.x86_64 libtirpc-1.3.4-1.rc3.fc41.x86_64 libtool-ltdl-2.4.7-10.fc40.x86_64 libunistring-1.1-7.fc41.x86_64 libutempter-1.2.1-13.fc40.x86_64 libuuid-2.40.1-1.fc41.x86_64 libverto-0.3.2-8.fc40.x86_64 libxcrypt-4.4.36-5.fc40.x86_64 libxml2-2.12.7-1.fc41.x86_64 libzstd-1.5.6-1.fc41.x86_64 lua-libs-5.4.6-5.fc40.x86_64 lua-srpm-macros-1-13.fc40.noarch lz4-libs-1.9.4-6.fc40.x86_64 mpfr-4.2.1-4.fc41.x86_64 ncurses-base-6.4-12.20240127.fc40.noarch ncurses-libs-6.4-12.20240127.fc40.x86_64 ocaml-srpm-macros-9-3.fc40.noarch openblas-srpm-macros-2-17.fc41.noarch openldap-2.6.7-1.fc40.x86_64 openssl-libs-3.2.1-6.fc41.x86_64 p11-kit-0.25.3-4.fc40.x86_64 p11-kit-trust-0.25.3-4.fc40.x86_64 package-notes-srpm-macros-0.5-11.fc40.noarch pam-1.6.1-1.fc41.x86_64 pam-libs-1.6.1-1.fc41.x86_64 patch-2.7.6-24.fc40.x86_64 pcre2-10.43-2.fc41.1.x86_64 pcre2-syntax-10.43-2.fc41.1.noarch perl-srpm-macros-1-53.fc40.noarch pkgconf-2.1.1-1.fc41.x86_64 pkgconf-m4-2.1.1-1.fc41.noarch pkgconf-pkg-config-2.1.1-1.fc41.x86_64 popt-1.19-6.fc40.x86_64 publicsuffix-list-dafsa-20240107-3.fc40.noarch pyproject-srpm-macros-1.12.0-1.fc40.noarch python-srpm-macros-3.12-9.fc41.noarch qt5-srpm-macros-5.15.13-1.fc41.noarch qt6-srpm-macros-6.7.0-1.fc41.noarch readline-8.2-8.fc40.x86_64 redhat-rpm-config-290-1.fc41.noarch rpm-4.19.1.1-2.fc41.x86_64 rpm-build-4.19.1.1-2.fc41.x86_64 rpm-build-libs-4.19.1.1-2.fc41.x86_64 rpm-libs-4.19.1.1-2.fc41.x86_64 rpm-sequoia-1.6.0-2.fc40.x86_64 rust-srpm-macros-26.3-1.fc41.noarch sed-4.9-1.fc40.x86_64 setup-2.14.5-2.fc40.noarch shadow-utils-4.15.1-5.fc41.x86_64 sqlite-libs-3.45.3-1.fc41.x86_64 systemd-libs-256~rc2-1.fc41.x86_64 tar-1.35-3.fc40.x86_64 unzip-6.0-63.fc40.x86_64 util-linux-2.40.1-1.fc41.x86_64 util-linux-core-2.40.1-1.fc41.x86_64 which-2.21-41.fc40.x86_64 xxhash-libs-0.8.2-2.fc40.x86_64 xz-5.4.6-3.fc41.x86_64 xz-libs-5.4.6-3.fc41.x86_64 zig-srpm-macros-1-2.fc40.noarch zip-3.0-40.fc40.x86_64 zlib-ng-compat-2.1.6-3.fc41.x86_64 zstd-1.5.6-1.fc41.x86_64 Start: buildsrpm Start: rpmbuild -bs warning: source_date_epoch_from_changelog set but %changelog is missing Building target platforms: x86_64 Building for target x86_64 Wrote: /builddir/build/SRPMS/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm RPM build warnings: source_date_epoch_from_changelog set but %changelog is missing Finish: rpmbuild -bs cp: preserving permissions for ‘/var/lib/copr-rpmbuild/results/chroot_scan/var/lib/mock/fedora-rawhide-x86_64-1716467991.378440/root/var/log’: No such file or directory INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-rawhide-x86_64-1716467991.378440/root/var/log/dnf5.log Finish: buildsrpm INFO: Done(/var/lib/copr-rpmbuild/workspace/workdir-g0rhv0d8/R-CRAN-RBesT/R-CRAN-RBesT.spec) Config(child) 0 minutes 11 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_success=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot INFO: Start(/var/lib/copr-rpmbuild/results/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm) Config(fedora-rawhide-x86_64) Start: chroot init INFO: mounting tmpfs at /var/lib/mock/fedora-rawhide-x86_64-1716467991.378440/root. INFO: calling preinit hooks INFO: enabled root cache Start: unpacking root cache Finish: unpacking root cache INFO: enabled package manager cache Start: cleaning package manager metadata Finish: cleaning package manager metadata INFO: enabled HW Info plugin INFO: Buildroot is handled by package management from host and used with --installroot: rpm-4.19.1.1-1.fc39.x86_64 rpm-sequoia-1.6.0-1.fc39.x86_64 python3-dnf-4.19.2-1.fc39.noarch python3-dnf-plugins-core-4.6.0-1.fc39.noarch yum-4.19.2-1.fc39.noarch dnf5-5.1.17-1.fc39.x86_64 dnf5-plugins-5.1.17-1.fc39.x86_64 Finish: chroot init Start: build phase for R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm Start: build setup for R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm warning: source_date_epoch_from_changelog set but %changelog is missing Building target platforms: x86_64 Building for target x86_64 Wrote: /builddir/build/SRPMS/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm RPM build warnings: source_date_epoch_from_changelog set but %changelog is missing Updating and loading repositories: fedora 100% | 130.3 KiB/s | 21.6 KiB | 00m00s Copr repository 100% | 90.4 KiB/s | 1.5 KiB | 00m00s Repositories loaded. Package Arch Version Repository Size Installing: R-CRAN-BH noarch 1.84.0.0-1.fc41.copr7349931 copr_base 121.0 MiB R-CRAN-Formula noarch 1.2.5-1.fc41.copr7350002 copr_base 205.4 KiB R-CRAN-Rcpp x86_64 1.0.12-1.fc41.copr7349917 copr_base 8.3 MiB R-CRAN-RcppEigen x86_64 0.3.4.0.0-1.fc41.copr7353593 copr_base 9.0 MiB R-CRAN-RcppParallel x86_64 5.1.7-1.fc41.copr7480144 copr_base 1.5 MiB R-CRAN-StanHeaders x86_64 2.32.8-1.fc41.copr7480260 copr_base 9.7 MiB R-CRAN-abind noarch 1.4.5-3.fc41.copr7349922 copr_base 92.0 KiB R-CRAN-assertthat noarch 0.2.1-3.fc41.copr7349935 copr_base 86.3 KiB R-CRAN-bayesplot noarch 1.11.1-1.fc41.copr7364930 copr_base 6.7 MiB R-CRAN-checkmate x86_64 2.3.1-1.fc41.copr7353592 copr_base 1.4 MiB R-CRAN-dplyr x86_64 1.1.4-1.fc41.copr7361225 copr_base 2.6 MiB R-CRAN-ggplot2 noarch 3.5.1-1.fc41.copr7361224 copr_base 7.1 MiB R-CRAN-matrixStats x86_64 1.3.0-1.fc41.copr7349920 copr_base 1.1 MiB R-CRAN-mvtnorm x86_64 1.2.5-1.fc41.copr7474908 copr_base 1.2 MiB R-CRAN-rlang x86_64 1.1.3-1.fc41.copr7349924 copr_base 2.6 MiB R-CRAN-rstan x86_64 2.32.6-1.fc41.copr7480261 copr_base 6.0 MiB R-CRAN-rstantools noarch 2.4.0-1.fc41.copr7356058 copr_base 304.0 KiB R-core x86_64 4.4.0-1.fc41~bootstrap copr_base 100.5 MiB R-devel x86_64 4.4.0-1.fc41~bootstrap copr_base 0.0 B Installing dependencies: R-CRAN-MASS x86_64 7.3.60.2-1.fc41.copr7382389 copr_base 1.8 MiB R-CRAN-Matrix x86_64 1.7.0-1.fc41.copr7382390 copr_base 8.0 MiB R-CRAN-QuickJSR x86_64 1.1.3-1.fc41.copr7355810 copr_base 2.7 MiB R-CRAN-R6 noarch 2.5.1-1.fc41.copr7349938 copr_base 115.9 KiB R-CRAN-RColorBrewer noarch 1.1.3-1.fc41.copr7349948 copr_base 63.6 KiB R-CRAN-backports x86_64 1.4.1-1.fc41.copr7349923 copr_base 180.8 KiB R-CRAN-callr noarch 3.7.6-1.fc41.copr7356069 copr_base 711.7 KiB R-CRAN-cli x86_64 3.6.2-1.fc41.copr7349961 copr_base 2.4 MiB R-CRAN-colorspace x86_64 2.1.0-1.fc41.copr7349953 copr_base 4.0 MiB R-CRAN-desc noarch 1.4.3-1.fc41.copr7353609 copr_base 514.2 KiB R-CRAN-distributional noarch 0.4.0-1.fc41.copr7358864 copr_base 649.1 KiB R-CRAN-fansi x86_64 1.0.6-1.fc41.copr7349952 copr_base 625.8 KiB R-CRAN-farver x86_64 2.1.2-1.fc41.copr7442181 copr_base 2.1 MiB R-CRAN-generics noarch 0.1.3-1.fc41.copr7350006 copr_base 160.2 KiB R-CRAN-ggridges noarch 0.5.6-1.fc41.copr7362419 copr_base 3.0 MiB R-CRAN-glue x86_64 1.7.0-1.fc41.copr7349919 copr_base 261.2 KiB R-CRAN-gridExtra noarch 2.3-3.fc41.copr7357925 copr_base 1.6 MiB R-CRAN-gtable noarch 0.3.5-1.fc41.copr7356060 copr_base 306.7 KiB R-CRAN-inline noarch 0.3.19-1.fc41.copr7349930 copr_base 211.0 KiB R-CRAN-isoband x86_64 0.2.7-1.fc41.copr7351195 copr_base 1.9 MiB R-CRAN-jsonlite x86_64 1.8.8-1.fc41.copr7349934 copr_base 2.3 MiB R-CRAN-labeling noarch 0.4.3-1.fc41.copr7349947 copr_base 92.7 KiB R-CRAN-lattice x86_64 0.22.6-1.fc41.copr7352639 copr_base 2.0 MiB R-CRAN-lifecycle noarch 1.0.4-1.fc41.copr7354340 copr_base 282.7 KiB R-CRAN-loo noarch 2.7.0-1.fc41.copr7362415 copr_base 2.7 MiB R-CRAN-magrittr x86_64 2.0.3-1.fc41.copr7349936 copr_base 417.3 KiB R-CRAN-mgcv x86_64 1.9.1-1.fc41.copr7357272 copr_base 4.5 MiB R-CRAN-munsell noarch 0.5.1-1.fc41.copr7353599 copr_base 379.0 KiB R-CRAN-nlme x86_64 3.1.164-1.fc41.copr7355272 copr_base 3.8 MiB R-CRAN-numDeriv noarch 2016.8.1.1-3.fc41.copr7350037 copr_base 151.0 KiB R-CRAN-pillar noarch 1.9.0-1.fc41.copr7357931 copr_base 1.4 MiB R-CRAN-pkgbuild noarch 1.4.4-1.fc41.copr7357929 copr_base 256.4 KiB R-CRAN-pkgconfig noarch 2.0.3-3.fc41.copr7349937 copr_base 34.0 KiB R-CRAN-plyr x86_64 1.8.9-1.fc41.copr7353597 copr_base 1.1 MiB R-CRAN-posterior noarch 1.5.0-1.fc41.copr7362018 copr_base 1.5 MiB R-CRAN-processx x86_64 3.8.4-1.fc41.copr7353601 copr_base 547.3 KiB R-CRAN-ps x86_64 1.7.6-1.fc41.copr7349956 copr_base 572.6 KiB R-CRAN-reshape2 x86_64 1.4.4-3.fc41.copr7359520 copr_base 215.1 KiB R-CRAN-scales noarch 1.3.0-1.fc41.copr7356067 copr_base 1.1 MiB R-CRAN-stringi x86_64 1.8.4-1.fc41.copr7422034 copr_base 2.0 MiB R-CRAN-stringr noarch 1.5.1-1.fc41.copr7357924 copr_base 646.8 KiB R-CRAN-tensorA x86_64 0.36.2.1-1.fc41.copr7350295 copr_base 381.7 KiB R-CRAN-tibble x86_64 3.2.1-1.fc41.copr7359525 copr_base 1.7 MiB R-CRAN-tidyselect noarch 1.2.1-1.fc41.copr7357928 copr_base 433.3 KiB R-CRAN-utf8 x86_64 1.2.4-1.fc41.copr7349954 copr_base 470.9 KiB R-CRAN-vctrs x86_64 0.6.5-1.fc41.copr7356070 copr_base 2.3 MiB R-CRAN-viridisLite noarch 0.4.2-1.fc41.copr7349928 copr_base 1.3 MiB R-CRAN-withr noarch 3.0.0-1.fc41.copr7349929 copr_base 420.0 KiB R-core-devel x86_64 4.4.0-1.fc41~bootstrap copr_base 394.1 KiB R-java x86_64 4.4.0-1.fc41~bootstrap copr_base 0.0 B R-java-devel x86_64 4.4.0-1.fc41~bootstrap copr_base 0.0 B R-littler x86_64 0.3.19-4.fc41 fedora 157.9 KiB R-rpm-macros noarch 1.2.1-10.fc41 fedora 5.6 KiB abattis-cantarell-vf-fonts noarch 0.301-12.fc40 fedora 192.7 KiB add-determinism x86_64 0.2.0-8.fc41 fedora 2.6 MiB alsa-lib x86_64 1.2.11-2.fc40 fedora 1.4 MiB annobin-docs noarch 12.54-2.fc41 fedora 96.2 KiB annobin-plugin-gcc x86_64 12.54-2.fc41 fedora 974.4 KiB avahi-libs x86_64 0.8-26.fc40 fedora 166.3 KiB brotli x86_64 1.1.0-3.fc40 fedora 31.8 KiB brotli-devel x86_64 1.1.0-3.fc40 fedora 65.6 KiB bzip2-devel x86_64 1.0.8-18.fc40 fedora 309.8 KiB cairo x86_64 1.18.0-3.fc40 fedora 1.7 MiB cairo-devel x86_64 1.18.0-3.fc40 fedora 2.3 MiB cmake-filesystem x86_64 3.28.3-4.fc41 fedora 0.0 B copy-jdk-configs noarch 4.1-5.fc40 fedora 20.3 KiB cpp x86_64 14.1.1-1.fc41 fedora 35.0 MiB crypto-policies-scripts noarch 20240521-1.gitf71d135.fc41 fedora 325.4 KiB cups-libs x86_64 1:2.4.8-3.fc41 fedora 618.9 KiB dbus-libs x86_64 1:1.14.10-3.fc40 fedora 368.9 KiB default-fonts-core-sans noarch 4.0-13.fc41 fedora 11.9 KiB desktop-file-utils x86_64 0.26-12.fc40 fedora 226.0 KiB emacs-filesystem noarch 1:30.0-2.fc41 fedora 0.0 B expat x86_64 2.6.2-1.fc41 fedora 280.8 KiB flexiblas x86_64 3.4.2-1.fc41 fedora 46.9 KiB flexiblas-devel x86_64 3.4.2-1.fc41 fedora 4.7 MiB flexiblas-netlib x86_64 3.4.2-1.fc41 fedora 10.4 MiB flexiblas-netlib64 x86_64 3.4.2-1.fc41 fedora 10.5 MiB flexiblas-openblas-openmp x86_64 3.4.2-1.fc41 fedora 39.3 KiB flexiblas-openblas-openmp64 x86_64 3.4.2-1.fc41 fedora 39.3 KiB fontconfig x86_64 2.15.0-5.fc41 fedora 767.9 KiB fontconfig-devel x86_64 2.15.0-5.fc41 fedora 117.2 KiB fonts-filesystem noarch 1:2.0.5-14.fc40 fedora 0.0 B freetype x86_64 2.13.2-5.fc40 fedora 842.6 KiB freetype-devel x86_64 2.13.2-5.fc40 fedora 7.8 MiB fribidi x86_64 1.0.14-1.fc41 fedora 359.6 KiB gc x86_64 8.2.2-6.fc40 fedora 258.7 KiB gcc x86_64 14.1.1-1.fc41 fedora 104.0 MiB gcc-c++ x86_64 14.1.1-1.fc41 fedora 38.1 MiB gcc-gfortran x86_64 14.1.1-1.fc41 fedora 37.2 MiB gcc-plugin-annobin x86_64 14.1.1-1.fc41 fedora 57.1 KiB gettext x86_64 0.22.5-2.fc41 fedora 5.2 MiB gettext-envsubst x86_64 0.22.5-2.fc41 fedora 74.9 KiB gettext-libs x86_64 0.22.5-2.fc41 fedora 1.7 MiB gettext-runtime x86_64 0.22.5-2.fc41 fedora 481.3 KiB glib2 x86_64 2.80.2-1.fc41 fedora 14.6 MiB glib2-devel x86_64 2.80.2-1.fc41 fedora 15.5 MiB glibc-devel x86_64 2.39.9000-18.fc41 fedora 37.7 KiB glibc-headers-x86 noarch 2.39.9000-18.fc41 fedora 2.2 MiB gnutls x86_64 3.8.5-2.fc41 fedora 3.2 MiB google-noto-fonts-common noarch 20240401-1.fc41 fedora 17.5 KiB google-noto-sans-vf-fonts noarch 20240401-1.fc41 fedora 1.2 MiB graphite2 x86_64 1.3.14-15.fc40 fedora 192.0 KiB graphite2-devel x86_64 1.3.14-15.fc40 fedora 49.1 KiB guile30 x86_64 3.0.9-1.fc41 fedora 52.7 MiB harfbuzz x86_64 8.4.0-1.fc41 fedora 2.6 MiB harfbuzz-devel x86_64 8.4.0-1.fc41 fedora 5.1 MiB harfbuzz-icu x86_64 8.4.0-1.fc41 fedora 15.5 KiB hwloc-libs x86_64 2.10.0-3.fc40 fedora 2.8 MiB java-21-openjdk x86_64 1:21.0.3.0.9-1.fc41 fedora 1.1 MiB java-21-openjdk-devel x86_64 1:21.0.3.0.9-1.fc41 fedora 11.2 MiB java-21-openjdk-headless x86_64 1:21.0.3.0.9-1.fc41 fedora 205.0 MiB javapackages-filesystem noarch 6.2.0-9.fc41 fedora 1.9 KiB jbigkit-libs x86_64 2.1-29.fc40 fedora 117.6 KiB kernel-headers x86_64 6.9.0-64.fc41 fedora 6.3 MiB libICE x86_64 1.1.1-3.fc40 fedora 181.2 KiB libRmath x86_64 4.4.0-1.fc41~bootstrap copr_base 242.8 KiB libRmath-devel x86_64 4.4.0-1.fc41~bootstrap copr_base 17.4 KiB libSM x86_64 1.2.4-3.fc40 fedora 97.3 KiB libX11 x86_64 1.8.9-1.fc41 fedora 1.3 MiB libX11-common noarch 1.8.9-1.fc41 fedora 1.1 MiB libX11-devel x86_64 1.8.9-1.fc41 fedora 1.0 MiB libX11-xcb x86_64 1.8.9-1.fc41 fedora 15.0 KiB libXau x86_64 1.0.11-6.fc40 fedora 66.9 KiB libXau-devel x86_64 1.0.11-6.fc40 fedora 6.4 KiB libXcomposite x86_64 0.4.6-3.fc40 fedora 44.5 KiB libXext x86_64 1.3.6-1.fc40 fedora 90.1 KiB libXext-devel x86_64 1.3.6-1.fc40 fedora 98.9 KiB libXft x86_64 2.3.8-6.fc40 fedora 164.5 KiB libXft-devel x86_64 2.3.8-6.fc40 fedora 31.7 KiB libXi x86_64 1.8.1-5.fc40 fedora 80.7 KiB libXmu x86_64 1.2.1-1.fc41 fedora 187.5 KiB libXrender x86_64 0.9.11-6.fc40 fedora 50.1 KiB libXrender-devel x86_64 0.9.11-6.fc40 fedora 50.1 KiB libXt x86_64 1.3.0-3.fc40 fedora 425.9 KiB libXtst x86_64 1.2.4-6.fc40 fedora 33.6 KiB libb2 x86_64 0.98.1-11.fc40 fedora 42.2 KiB libblkid-devel x86_64 2.40.1-1.fc41 fedora 44.9 KiB libdatrie x86_64 0.2.13-9.fc40 fedora 57.9 KiB libffi-devel x86_64 3.4.6-1.fc41 fedora 33.1 KiB libfontenc x86_64 1.1.8-1.fc41 fedora 67.0 KiB libgfortran x86_64 14.1.1-1.fc41 fedora 2.9 MiB libicu x86_64 74.2-1.fc40 fedora 34.9 MiB libicu-devel x86_64 74.2-1.fc40 fedora 5.6 MiB libjpeg-turbo x86_64 3.0.2-2.fc41 fedora 772.9 KiB liblerc x86_64 4.0.0-6.fc40 fedora 603.5 KiB libmount-devel x86_64 2.40.1-1.fc41 fedora 63.5 KiB libmpc x86_64 1.3.1-5.fc40 fedora 164.7 KiB libpng x86_64 2:1.6.40-3.fc40 fedora 241.8 KiB libpng-devel x86_64 2:1.6.40-3.fc40 fedora 881.5 KiB libquadmath x86_64 14.1.1-1.fc41 fedora 325.9 KiB libquadmath-devel x86_64 14.1.1-1.fc41 fedora 21.8 KiB libselinux-devel x86_64 3.6-4.fc40 fedora 126.1 KiB libsepol-devel x86_64 3.6-3.fc40 fedora 120.2 KiB libstdc++-devel x86_64 14.1.1-1.fc41 fedora 15.4 MiB libtextstyle x86_64 0.22.5-2.fc41 fedora 195.6 KiB libthai x86_64 0.1.29-8.fc40 fedora 783.5 KiB libtiff x86_64 4.6.0-2.fc40 fedora 1.1 MiB libtirpc-devel x86_64 1.3.4-1.rc3.fc41 fedora 251.6 KiB libwebp x86_64 1.4.0-1.fc41 fedora 802.7 KiB libxcb x86_64 1.17.0-1.fc41 fedora 1.1 MiB libxcb-devel x86_64 1.17.0-1.fc41 fedora 2.7 MiB libxcrypt-devel x86_64 4.4.36-5.fc40 fedora 30.3 KiB libxml2-devel x86_64 2.12.7-1.fc41 fedora 3.4 MiB lksctp-tools x86_64 1.0.19-8.fc41 fedora 275.2 KiB lua x86_64 5.4.6-5.fc40 fedora 597.8 KiB lua-posix x86_64 36.2.1-6.fc40 fedora 599.7 KiB make x86_64 1:4.4.1-6.fc40 fedora 1.8 MiB mkfontscale x86_64 1.2.2-6.fc40 fedora 49.2 KiB mpdecimal x86_64 2.5.1-9.fc40 fedora 200.9 KiB nettle x86_64 3.9.1-6.fc40 fedora 790.1 KiB nspr x86_64 4.35.0-22.fc41 fedora 312.7 KiB nss x86_64 3.99.0-1.fc41 fedora 1.9 MiB nss-softokn x86_64 3.99.0-1.fc41 fedora 1.9 MiB nss-softokn-freebl x86_64 3.99.0-1.fc41 fedora 896.6 KiB nss-sysinit x86_64 3.99.0-1.fc41 fedora 18.2 KiB nss-util x86_64 3.99.0-1.fc41 fedora 226.1 KiB openblas x86_64 0.3.26-4.fc40 fedora 96.0 KiB openblas-openmp x86_64 0.3.26-4.fc40 fedora 38.9 MiB openblas-openmp64 x86_64 0.3.26-4.fc40 fedora 39.1 MiB pango x86_64 1.52.2-1.fc41 fedora 995.8 KiB pcre2-devel x86_64 10.43-2.fc41.1 fedora 2.0 MiB pcre2-utf16 x86_64 10.43-2.fc41.1 fedora 590.0 KiB pcre2-utf32 x86_64 10.43-2.fc41.1 fedora 557.9 KiB pixman x86_64 0.43.4-1.fc41 fedora 710.1 KiB pixman-devel x86_64 0.43.4-1.fc41 fedora 49.4 KiB python-pip-wheel noarch 24.0-2.fc41 fedora 1.5 MiB python3 x86_64 3.12.3-2.fc41 fedora 31.5 KiB python3-libs x86_64 3.12.3-2.fc41 fedora 40.9 MiB python3-packaging noarch 24.0-1.fc41 fedora 424.8 KiB sysprof-capture-devel x86_64 46.0-1.fc41 fedora 252.8 KiB tbb x86_64 2021.11.0-5.fc40 fedora 440.9 KiB tbb-bind x86_64 2021.11.0-5.fc40 fedora 23.7 KiB tbb-devel x86_64 2021.11.0-5.fc40 fedora 1.3 MiB tcl x86_64 1:8.6.14-1.fc41 fedora 4.2 MiB tcl-devel x86_64 1:8.6.14-1.fc41 fedora 791.4 KiB tk x86_64 1:8.6.14-1.fc41 fedora 3.6 MiB tk-devel x86_64 1:8.6.14-1.fc41 fedora 985.0 KiB tre x86_64 0.8.0-43.20140228gitc2f5d13.fc40 fedora 75.9 KiB tre-common noarch 0.8.0-43.20140228gitc2f5d13.fc40 fedora 81.0 KiB tre-devel x86_64 0.8.0-43.20140228gitc2f5d13.fc40 fedora 10.7 KiB ttmkfdir x86_64 3.0.9-70.fc40 fedora 122.7 KiB tzdata noarch 2024a-7.fc41 fedora 1.6 MiB tzdata-java noarch 2024a-7.fc41 fedora 101.7 KiB xdg-utils noarch 1.2.1-1.fc41 fedora 346.3 KiB xml-common noarch 0.6.3-63.fc40 fedora 78.4 KiB xorg-x11-fonts-Type1 noarch 7.5-38.fc40 fedora 863.3 KiB xorg-x11-proto-devel noarch 2024.1-1.fc41 fedora 1.7 MiB xz-devel x86_64 1:5.4.6-3.fc41 fedora 255.8 KiB zlib-ng-compat-devel x86_64 2.1.6-3.fc41 fedora 103.4 KiB Transaction Summary: Installing: 229 packages Total size of inbound packages is 352 MiB. Need to download 352 MiB. After this operation 1 GiB will be used (install 1 GiB, remove 0 B). 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R-CRAN-scales-0:1.3.0-1.fc41. 100% | 137.5 MiB/s | 704.1 KiB | 00m00s [ 40/229] R-CRAN-withr-0:3.0.0-1.fc41.c 100% | 65.1 MiB/s | 266.8 KiB | 00m00s [ 41/229] R-CRAN-QuickJSR-0:1.1.3-1.fc4 100% | 106.3 MiB/s | 761.7 KiB | 00m00s [ 42/229] R-CRAN-gridExtra-0:2.3-3.fc41 100% | 90.9 MiB/s | 1.0 MiB | 00m00s [ 43/229] R-CRAN-inline-0:0.3.19-1.fc41 100% | 23.6 MiB/s | 144.9 KiB | 00m00s [ 44/229] R-CRAN-pkgbuild-0:1.4.4-1.fc4 100% | 51.2 MiB/s | 209.7 KiB | 00m00s [ 45/229] R-CRAN-loo-0:2.7.0-1.fc41.cop 100% | 123.7 MiB/s | 1.7 MiB | 00m00s [ 46/229] R-CRAN-desc-0:1.4.3-1.fc41.co 100% | 34.3 MiB/s | 351.3 KiB | 00m00s [ 47/229] cairo-0:1.18.0-3.fc40.x86_64 100% | 230.8 MiB/s | 708.9 KiB | 00m00s [ 48/229] R-rpm-macros-0:1.2.1-10.fc41. 100% | 2.7 MiB/s | 11.2 KiB | 00m00s [ 49/229] libX11-0:1.8.9-1.fc41.x86_64 100% | 90.4 MiB/s | 647.8 KiB | 00m00s [ 50/229] glib2-0:2.80.2-1.fc41.x86_64 100% | 302.9 MiB/s | 3.0 MiB | 00m00s [ 51/229] libXmu-0:1.2.1-1.fc41.x86_64 100% | 19.0 MiB/s | 77.6 KiB 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libX11-common-0:1.8.9-1.fc41. 100% | 57.3 MiB/s | 176.1 KiB | 00m00s [ 91/229] freetype-0:2.13.2-5.fc40.x86_ 100% | 44.5 MiB/s | 409.7 KiB | 00m00s [ 92/229] libSM-0:1.2.4-3.fc40.x86_64 100% | 42.0 MiB/s | 43.0 KiB | 00m00s [ 93/229] libICE-0:1.1.1-3.fc40.x86_64 100% | 36.4 MiB/s | 74.5 KiB | 00m00s [ 94/229] jbigkit-libs-0:2.1-29.fc40.x8 100% | 25.9 MiB/s | 53.1 KiB | 00m00s [ 95/229] liblerc-0:4.0.0-6.fc40.x86_64 100% | 68.4 MiB/s | 210.1 KiB | 00m00s [ 96/229] libwebp-0:1.4.0-1.fc41.x86_64 100% | 94.7 MiB/s | 290.9 KiB | 00m00s [ 97/229] harfbuzz-0:8.4.0-1.fc41.x86_6 100% | 336.0 MiB/s | 1.0 MiB | 00m00s [ 98/229] fribidi-0:1.0.14-1.fc41.x86_6 100% | 17.8 MiB/s | 91.3 KiB | 00m00s [ 99/229] libXft-0:2.3.8-6.fc40.x86_64 100% | 35.2 MiB/s | 72.1 KiB | 00m00s [100/229] desktop-file-utils-0:0.26-12. 100% | 66.6 MiB/s | 68.2 KiB | 00m00s [101/229] tre-common-0:0.8.0-43.2014022 100% | 15.2 MiB/s | 31.2 KiB | 00m00s [102/229] libthai-0:0.1.29-8.fc40.x86_6 100% | 69.6 MiB/s | 213.8 KiB | 00m00s [103/229] R-CRAN-numDeriv-0:2016.8.1.1- 100% | 62.6 MiB/s | 128.2 KiB | 00m00s [104/229] R-CRAN-stringi-0:1.8.4-1.fc41 100% | 163.9 MiB/s | 1.0 MiB | 00m00s [105/229] R-CRAN-lattice-0:0.22.6-1.fc4 100% | 178.3 MiB/s | 1.4 MiB | 00m00s [106/229] openblas-openmp-0:0.3.26-4.fc 100% | 240.9 MiB/s | 5.1 MiB | 00m00s [107/229] R-CRAN-colorspace-0:2.1.0-1.f 100% | 152.0 MiB/s | 2.4 MiB | 00m00s [108/229] R-CRAN-ps-0:1.7.6-1.fc41.copr 100% | 29.8 MiB/s | 336.1 KiB | 00m00s [109/229] default-fonts-core-sans-0:4.0 100% | 15.4 MiB/s | 31.5 KiB | 00m00s [110/229] fonts-filesystem-1:2.0.5-14.f 100% | 8.0 MiB/s | 8.2 KiB | 00m00s [111/229] xml-common-0:0.6.3-63.fc40.no 100% | 30.3 MiB/s | 31.0 KiB | 00m00s [112/229] libXau-0:1.0.11-6.fc40.x86_64 100% | 31.0 MiB/s | 31.7 KiB | 00m00s [113/229] nettle-0:3.9.1-6.fc40.x86_64 100% | 207.5 MiB/s | 424.9 KiB | 00m00s [114/229] graphite2-0:1.3.14-15.fc40.x8 100% | 46.3 MiB/s | 94.8 KiB | 00m00s [115/229] libdatrie-0:0.2.13-9.fc40.x86 100% | 10.4 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| 6.5 MiB/s | 39.7 KiB | 00m00s [129/229] libXtst-0:1.2.4-6.fc40.x86_64 100% | 6.7 MiB/s | 20.4 KiB | 00m00s [130/229] xorg-x11-fonts-Type1-0:7.5-38 100% | 82.1 MiB/s | 504.1 KiB | 00m00s [131/229] alsa-lib-0:1.2.11-2.fc40.x86_ 100% | 83.6 MiB/s | 513.9 KiB | 00m00s [132/229] copy-jdk-configs-0:4.1-5.fc40 100% | 6.7 MiB/s | 27.6 KiB | 00m00s [133/229] javapackages-filesystem-0:6.2 100% | 3.0 MiB/s | 12.3 KiB | 00m00s [134/229] lksctp-tools-0:1.0.19-8.fc41. 100% | 23.9 MiB/s | 97.8 KiB | 00m00s [135/229] tzdata-java-0:2024a-7.fc41.no 100% | 23.1 MiB/s | 47.4 KiB | 00m00s [136/229] mkfontscale-0:1.2.2-6.fc40.x8 100% | 15.5 MiB/s | 31.8 KiB | 00m00s [137/229] ttmkfdir-0:3.0.9-70.fc40.x86_ 100% | 13.7 MiB/s | 56.0 KiB | 00m00s [138/229] lua-posix-0:36.2.1-6.fc40.x86 100% | 46.4 MiB/s | 142.4 KiB | 00m00s [139/229] libfontenc-0:1.1.8-1.fc41.x86 100% | 31.6 MiB/s | 32.4 KiB | 00m00s [140/229] bzip2-devel-0:1.0.8-18.fc40.x 100% | 41.7 MiB/s | 213.5 KiB | 00m00s [141/229] flexiblas-devel-0:3.4.2-1.fc4 100% | 23.6 MiB/s | 121.0 KiB | 00m00s [142/229] flexiblas-openblas-openmp64-0 100% | 4.3 MiB/s | 17.7 KiB | 00m00s [143/229] flexiblas-netlib64-0:3.4.2-1. 100% | 101.1 MiB/s | 3.0 MiB | 00m00s [144/229] openblas-openmp64-0:0.3.26-4. 100% | 102.9 MiB/s | 4.9 MiB | 00m00s [145/229] gcc-0:14.1.1-1.fc41.x86_64 100% | 278.3 MiB/s | 37.0 MiB | 00m00s [146/229] gcc-c++-0:14.1.1-1.fc41.x86_6 100% | 81.4 MiB/s | 14.2 MiB | 00m00s [147/229] libmpc-0:1.3.1-5.fc40.x86_64 100% | 3.0 MiB/s | 71.1 KiB | 00m00s [148/229] gcc-plugin-annobin-0:14.1.1-1 100% | 16.3 MiB/s | 50.2 KiB | 00m00s [149/229] annobin-plugin-gcc-0:12.54-2. 100% | 41.0 MiB/s | 964.7 KiB | 00m00s [150/229] annobin-docs-0:12.54-2.fc41.n 100% | 2.7 MiB/s | 89.8 KiB | 00m00s [151/229] java-21-openjdk-headless-1:21 100% | 134.1 MiB/s | 47.7 MiB | 00m00s [152/229] libRmath-devel-0:4.4.0-1.fc41 100% | 8.0 MiB/s | 16.3 KiB | 00m00s [153/229] cpp-0:14.1.1-1.fc41.x86_64 100% | 107.6 MiB/s | 11.9 MiB | 00m00s 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libtextstyle-0:0.22.5-2.fc41. 100% | 43.3 MiB/s | 88.7 KiB | 00m00s [180/229] gettext-envsubst-0:0.22.5-2.f 100% | 18.6 MiB/s | 38.0 KiB | 00m00s [181/229] libXrender-devel-0:0.9.11-6.f 100% | 9.3 MiB/s | 19.0 KiB | 00m00s [182/229] freetype-devel-0:2.13.2-5.fc4 100% | 84.4 MiB/s | 951.2 KiB | 00m00s [183/229] cups-libs-1:2.4.8-3.fc41.x86_ 100% | 63.2 MiB/s | 259.0 KiB | 00m00s [184/229] avahi-libs-0:0.8-26.fc40.x86_ 100% | 16.2 MiB/s | 66.5 KiB | 00m00s [185/229] libxcb-devel-0:1.17.0-1.fc41. 100% | 79.9 MiB/s | 1.4 MiB | 00m00s [186/229] dbus-libs-1:1.14.10-3.fc40.x8 100% | 76.3 MiB/s | 156.3 KiB | 00m00s [187/229] nss-0:3.99.0-1.fc41.x86_64 100% | 171.8 MiB/s | 703.8 KiB | 00m00s [188/229] crypto-policies-scripts-0:202 100% | 29.3 MiB/s | 120.2 KiB | 00m00s [189/229] nspr-0:4.35.0-22.fc41.x86_64 100% | 134.2 MiB/s | 137.4 KiB | 00m00s [190/229] nss-softokn-0:3.99.0-1.fc41.x 100% | 133.3 MiB/s | 409.5 KiB | 00m00s [191/229] nss-sysinit-0:3.99.0-1.fc41.x 100% | 9.1 MiB/s | 18.7 KiB | 00m00s [192/229] nss-util-0:3.99.0-1.fc41.x86_ 100% | 86.1 MiB/s | 88.2 KiB | 00m00s [193/229] nss-softokn-freebl-0:3.99.0-1 100% | 188.4 MiB/s | 385.9 KiB | 00m00s [194/229] libquadmath-devel-0:14.1.1-1. 100% | 12.7 MiB/s | 39.0 KiB | 00m00s [195/229] glibc-devel-0:2.39.9000-18.fc 100% | 61.7 MiB/s | 126.4 KiB | 00m00s [196/229] glibc-headers-x86-0:2.39.9000 100% | 120.6 MiB/s | 617.6 KiB | 00m00s [197/229] libxcrypt-devel-0:4.4.36-5.fc 100% | 7.0 MiB/s | 28.6 KiB | 00m00s [198/229] libstdc++-devel-0:14.1.1-1.fc 100% | 119.3 MiB/s | 2.7 MiB | 00m00s [199/229] brotli-devel-0:1.1.0-3.fc40.x 100% | 4.1 MiB/s | 33.8 KiB | 00m00s [200/229] brotli-0:1.1.0-3.fc40.x86_64 100% | 6.5 MiB/s | 19.9 KiB | 00m00s [201/229] harfbuzz-devel-0:8.4.0-1.fc41 100% | 88.1 MiB/s | 451.0 KiB | 00m00s [202/229] harfbuzz-icu-0:8.4.0-1.fc41.x 100% | 2.6 MiB/s | 16.1 KiB | 00m00s [203/229] libpng-devel-2:1.6.40-3.fc40. 100% | 35.5 MiB/s | 290.6 KiB | 00m00s [204/229] libxml2-devel-0:2.12.7-1.fc41 100% | 56.9 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-------------------------------------------------------------------------------- [229/229] Total 100% | 237.8 MiB/s | 352.1 MiB | 00m01s Running transaction [ 1/231] Verify package files 100% | 202.0 B/s | 229.0 B | 00m01s >>> Running pre-transaction scriptlet: crypto-policies-scripts-0:20240521-1.gitf >>> Stop pre-transaction scriptlet: crypto-policies-scripts-0:20240521-1.gitf71d >>> Running pre-transaction scriptlet: copy-jdk-configs-0:4.1-5.fc40.noarch >>> Stop pre-transaction scriptlet: copy-jdk-configs-0:4.1-5.fc40.noarch >>> Running pre-transaction scriptlet: java-21-openjdk-headless-1:21.0.3.0.9-1.f >>> Stop pre-transaction scriptlet: java-21-openjdk-headless-1:21.0.3.0.9-1.fc41 [ 2/231] Prepare transaction 100% | 1.0 KiB/s | 229.0 B | 00m00s [ 3/231] Installing zlib-ng-compat-dev 100% | 102.0 MiB/s | 104.5 KiB | 00m00s [ 4/231] Installing nspr-0:4.35.0-22.f 100% | 153.6 MiB/s | 314.5 KiB | 00m00s [ 5/231] Installing xorg-x11-proto-dev 100% | 297.1 MiB/s | 1.8 MiB | 00m00s [ 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>>> Running post-install scriptlet: java-21-openjdk-headless-1:21.0.3.0.9-1.fc41 >>> Stop post-install scriptlet: java-21-openjdk-headless-1:21.0.3.0.9-1.fc41.x8 >>> Running pre-install scriptlet: xml-common-0:0.6.3-63.fc40.noarch >>> Stop pre-install scriptlet: xml-common-0:0.6.3-63.fc40.noarch [117/231] Installing xml-common-0:0.6.3 100% | 79.2 MiB/s | 81.1 KiB | 00m00s [118/231] Installing tre-common-0:0.8.0 100% | 81.2 MiB/s | 83.1 KiB | 00m00s [119/231] Installing tre-0:0.8.0-43.201 100% | 74.9 MiB/s | 76.7 KiB | 00m00s [120/231] Installing tre-devel-0:0.8.0- 100% | 0.0 B/s | 11.6 KiB | 00m00s [121/231] Installing fribidi-0:1.0.14-1 100% | 176.8 MiB/s | 362.1 KiB | 00m00s [122/231] Installing libwebp-0:1.4.0-1. 100% | 262.6 MiB/s | 806.8 KiB | 00m00s [123/231] Installing liblerc-0:4.0.0-6. 100% | 295.4 MiB/s | 605.0 KiB | 00m00s [124/231] Installing jbigkit-libs-0:2.1 100% | 116.8 MiB/s | 119.6 KiB | 00m00s [125/231] Installing libtiff-0:4.6.0-2. 100% | 279.9 MiB/s | 1.1 MiB | 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Finish: build setup for R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm Start: rpmbuild R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm warning: source_date_epoch_from_changelog set but %changelog is missing Building target platforms: x86_64 Building for target x86_64 Executing(%prep): /bin/sh -e /var/tmp/rpm-tmp.so9xoJ + umask 022 + cd /builddir/build/BUILD + cd /builddir/build/BUILD + rm -rf RBesT + /usr/bin/mkdir -p RBesT + cd RBesT + /usr/lib/rpm/rpmuncompress -x /builddir/build/SOURCES/RBesT_1.7-3.tar.gz + STATUS=0 + '[' 0 -ne 0 ']' + rm -rf /builddir/build/BUILD/RBesT-SPECPARTS + /usr/bin/mkdir -p /builddir/build/BUILD/RBesT-SPECPARTS + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w . + find -type f -executable -exec grep -Iq . '{}' ';' -exec sed -i -e '$a\' '{}' ';' + '[' -d RBesT/src ']' + find RBesT/src -type f -exec sed -i s@/usr/bin/strip@/usr/bin/true@g '{}' ';' + '[' -d RBesT/src ']' + find RBesT/src/Makevars -type f -exec sed -i s@-g0@@g '{}' ';' + find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' '{}' ';' + RPM_EC=0 ++ jobs -p + exit 0 Executing(%build): /bin/sh -e /var/tmp/rpm-tmp.8r47KG + umask 022 + cd /builddir/build/BUILD + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd RBesT + RPM_EC=0 ++ jobs -p + exit 0 Executing(%install): /bin/sh -e /var/tmp/rpm-tmp.TCO71B + umask 022 + cd /builddir/build/BUILD + '[' /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 '!=' / ']' + rm -rf /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 ++ dirname /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 + mkdir -p /builddir/build/BUILDROOT + mkdir /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 + CFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CFLAGS + CXXFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer ' + export CXXFLAGS + FFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FFLAGS + FCFLAGS='-O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -I/usr/lib64/gfortran/modules ' + export FCFLAGS + VALAFLAGS=-g + export VALAFLAGS + RUSTFLAGS='-Copt-level=3 -Cdebuginfo=2 -Ccodegen-units=1 -Cstrip=none -Cforce-frame-pointers=yes -Clink-arg=-specs=/usr/lib/rpm/redhat/redhat-package-notes --cap-lints=warn' + export RUSTFLAGS + LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -specs=/usr/lib/rpm/redhat/redhat-package-notes ' + export LDFLAGS + LT_SYS_LIBRARY_PATH=/usr/lib64: + export LT_SYS_LIBRARY_PATH + CC=gcc + export CC + CXX=g++ + export CXX + cd RBesT + mkdir -p /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64/usr/local/lib/R/library + /usr/bin/R CMD INSTALL -l /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64/usr/local/lib/R/library RBesT * installing *source* package ‘RBesT’ ... ** package ‘RBesT’ successfully unpacked and MD5 sums checked ** using staged installation ** libs using C++ compiler: ‘g++ (GCC) 14.1.1 20240507 (Red Hat 14.1.1-1)’ using C++17 g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c RcppExports.cpp -o RcppExports.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/RcppEigen/include/RcppEigenForward.h:28, from /usr/local/lib/R/library/RcppEigen/include/RcppEigen.h:25, from RcppExports.cpp:4: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/RcppEigen/include/RcppEigenForward.h:29: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ g++ -std=gnu++17 -I"/usr/include/R" -DNDEBUG -I"../inst/include" -I"/usr/local/lib/R/library/StanHeaders/include/src" -DBOOST_DISABLE_ASSERTS -DEIGEN_NO_DEBUG -DBOOST_MATH_OVERFLOW_ERROR_POLICY=errno_on_error -DUSE_STANC3 -D_HAS_AUTO_PTR_ETC=0 -I'/usr/local/lib/R/library/BH/include' -I'/usr/local/lib/R/library/Rcpp/include' -I'/usr/local/lib/R/library/RcppEigen/include' -I'/usr/local/lib/R/library/RcppParallel/include' -I'/usr/local/lib/R/library/rstan/include' -I'/usr/local/lib/R/library/StanHeaders/include' -I/usr/local/include -I/usr/include/oneapi -DTBB_INTERFACE_NEW -I'/usr/local/lib/R/library/RcppParallel/include' -D_REENTRANT -DSTAN_THREADS -DTBB_INTERFACE_NEW -fpic -O2 -flto=auto -ffat-lto-objects -fexceptions -g -grecord-gcc-switches -pipe -Wall -Werror=format-security -Wp,-U_FORTIFY_SOURCE,-D_FORTIFY_SOURCE=3 -Wp,-D_GLIBCXX_ASSERTIONS -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1 -fstack-protector-strong -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -m64 -march=x86-64 -mtune=generic -fasynchronous-unwind-tables -fstack-clash-protection -fcf-protection -mtls-dialect=gnu2 -fno-omit-frame-pointer -mno-omit-leaf-frame-pointer -c stanExports_gMAP.cc -o stanExports_gMAP.o In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:205, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Dense:1, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:3, from stanExports_gMAP.h:18, from stanExports_gMAP.cc:5: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:46:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 46 | typedef eigen_packet_wrapper<__m128i, 0> Packet4i; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:47:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 47 | typedef eigen_packet_wrapper<__m128i, 1> Packet16b; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:49:39: warning: ignoring attributes on template argument ‘__m128’ [-Wignored-attributes] 49 | template<> struct is_arithmetic<__m128> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:50:40: warning: ignoring attributes on template argument ‘__m128i’ [-Wignored-attributes] 50 | template<> struct is_arithmetic<__m128i> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:51:40: warning: ignoring attributes on template argument ‘__m128d’ [-Wignored-attributes] 51 | template<> struct is_arithmetic<__m128d> { enum { value = true }; }; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:222:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 222 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:228:43: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 228 | template<> struct unpacket_traits { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1124:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 1124 | ptranspose(PacketBlock& kernel) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/PacketMath.h:1129:34: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 1129 | ptranspose(PacketBlock& kernel) { | ^ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:174: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__m128’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:173:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 173 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:16:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 16 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/Default/ConjHelper.h:29:60: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__m128d’} [-Wignored-attributes] 29 | struct conj_helper { \ | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/arch/SSE/Complex.h:298:1: note: in expansion of macro ‘EIGEN_MAKE_CONJ_HELPER_CPLX_REAL’ 298 | EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:165: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(4) float>::half’ {aka ‘__m128’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:271: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from ‘struct Eigen::internal::traits >’ 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from ‘class Eigen::QuaternionBase >’ 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from ‘class Eigen::Quaternion’ 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:18, from /usr/local/lib/R/library/BH/include/boost/shared_ptr.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/time_clock.hpp:17, from /usr/local/lib/R/library/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:15, from /usr/local/lib/R/library/rstan/include/rstan/rstaninc.hpp:4: /usr/local/lib/R/library/BH/include/boost/smart_ptr/detail/shared_count.hpp:361:33: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 361 | explicit shared_count( std::auto_ptr & r ): pi_( new sp_counted_impl_p( r.get() ) ) | ^~~~~~~~ In file included from /usr/include/c++/14/memory:78, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:7: /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:251:65: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 251 | template< class T, class R > struct sp_enable_if_auto_ptr< std::auto_ptr< T >, R > | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:508:31: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 508 | explicit shared_ptr( std::auto_ptr & r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:521:22: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 521 | shared_ptr( std::auto_ptr && r ): px(r.get()), pn() | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:604:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 604 | shared_ptr & operator=( std::auto_ptr & r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:613:34: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 613 | shared_ptr & operator=( std::auto_ptr && r ) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function ‘boost::shared_ptr& boost::shared_ptr::operator=(std::auto_ptr<_Up>&&)’: /usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:615:38: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 615 | this_type( static_cast< std::auto_ptr && >( r ) ).swap( *this ); | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/SparseCore:37, from /usr/local/lib/R/library/RcppEigen/include/Eigen/Sparse:26, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from ‘class Eigen::SparseMatrix’ 96 | class SparseMatrix | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from ‘struct Eigen::internal::traits > >’ 19 | template struct traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from ‘class Eigen::SolverBase > >’ 68 | class SolverBase : public EigenBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from ‘class Eigen::LDLT >’ 59 | template class LDLT | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from ‘class Eigen::LDLT >’ 69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from ‘class Eigen::LDLT >’ 287 | TmpMatrixType m_temporary; | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:46:15: required from here 46 | if (cholesky.info() != Eigen::Success || !cholesky.isPositive() | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:29: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:41: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:47:45: required from here 47 | || (cholesky.vectorD().array() <= 0.0).any()) { | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:26: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply_lower_tri_self_transpose.hpp:35:34: required from here 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_array.hpp:37:49: required from here 37 | Eigen::VectorXd v = Eigen::VectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:28: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/linspaced_row_vector.hpp:32:39: required from here 32 | return Eigen::RowVectorXd::LinSpaced(K, low, high); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:53: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:72: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:77: required from here 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:17: required from here 71 | A.diagonal().array() -= mu; | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:71:29: required from here 71 | A.diagonal().array() -= mu; | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:86:43: required from here 86 | bi = (t / (s * (j + 1))) * (A * bi); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:22: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:38: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:178:58: required from here 178 | alpha = Eigen::VectorXd::Constant(_p_max - 1, normA); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from ‘stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]’ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from ‘auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]’ 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:197:41: required from here 197 | Eigen::MatrixXd c = stan::math::ceil(mt) * u.asDiagonal(); | ~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::internal::member_minCoeff, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::internal::member_minCoeff, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::internal::member_minCoeff, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from ‘class Eigen::PartialReduxExpr, Eigen::internal::member_minCoeff, 0>’ 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:203:38: required from here 203 | int cost = c.colwise().minCoeff().minCoeff(&m); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/one_hot_row_vector.hpp:25:52: required from here 25 | Eigen::RowVectorXd ret = Eigen::RowVectorXd::Zero(K); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:13:64: required from here 13 | : m_(Eigen::VectorXd::Zero(n)), m2_(Eigen::MatrixXd::Zero(n, n)) { | ~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:26:31: required from here 26 | Eigen::VectorXd delta(q - m_); | ^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:38: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:37:40: required from here 37 | covar = m2_ / (num_samples_ - 1.0); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_var_estimator.hpp:28:30: required from here 28 | m2_ += delta.cwiseProduct(q - m_); | ~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here 77 | Eigen::Map(dz_dt.data(), dz_dt.size()) = f_y_t; | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:13, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:43: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combination(std::vector&, const int&, const int&, const int&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:73:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 73 | for (std::size_t i = 0; i < p - 1; i++) { | ~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:79:16: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 79 | } while (k < x); | ~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::combos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:102:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 102 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:105:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 105 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::increment(std::vector&, const int&, const double&, const std::vector&, std::vector&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:126:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘const int’ [-Wsign-compare] 126 | for (std::size_t j = 0; j != k; j++) { | ~~^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 132 | while ((first_zero < index.size()) && index[first_zero]) { | ~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 135 | if (first_zero == index.size()) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:143:31: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 143 | for (std::size_t i = 0; i != first_zero + 1; i++) { | ~~^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function ‘void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector >&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:168:29: warning: comparison of integer expressions of different signedness: ‘std::size_t’ {aka ‘long unsigned int’} and ‘int’ [-Wsign-compare] 168 | for (std::size_t i = 1; i != choose_dimk + 1; i++) { | ~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here 40 | coupled_state.size()); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/mpl/aux_/na_assert.hpp:23, from /usr/local/lib/R/library/BH/include/boost/mpl/arg.hpp:25, from /usr/local/lib/R/library/BH/include/boost/mpl/placeholders.hpp:24, from /usr/local/lib/R/library/BH/include/boost/mpl/apply.hpp:24, from /usr/local/lib/R/library/BH/include/boost/serialization/array_optimization.hpp:18, from /usr/local/lib/R/library/BH/include/boost/serialization/array_wrapper.hpp:21, from /usr/local/lib/R/library/BH/include/boost/serialization/array.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:22, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/vector.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint.hpp:25, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor.hpp:16: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp: At global scope: /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: warning: unnecessary parentheses in declaration of ‘assert_arg’ [-Wparentheses] 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ | - 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ | - /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of ‘assert_not_arg’ [-Wparentheses] 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ /usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | - 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ | - In file included from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/traits.hpp:21, from /usr/local/lib/R/library/BH/include/boost/numeric/ublas/storage.hpp:27: /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:111:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 111 | public std::iterator { | ^~~~~~~~ In file included from /usr/include/c++/14/bits/stl_algobase.h:65, from /usr/include/c++/14/bits/specfun.h:43, from /usr/include/c++/14/cmath:3898, from /usr/local/lib/R/library/Rcpp/include/Rcpp/platform/compiler.h:100, from /usr/local/lib/R/library/Rcpp/include/Rcpp/r/headers.h:62, from /usr/local/lib/R/library/Rcpp/include/RcppCommon.h:30, from /usr/local/lib/R/library/Rcpp/include/Rcpp.h:27, from stanExports_gMAP.cc:3: /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:149:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 149 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/numeric/ublas/detail/iterator.hpp:204:21: warning: ‘template struct std::iterator’ is deprecated [-Wdeprecated-declarations] 204 | public std::iterator { | ^~~~~~~~ /usr/include/c++/14/bits/stl_iterator_base_types.h:127:34: note: declared here 127 | struct _GLIBCXX17_DEPRECATED iterator | ^~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/invocation/invoke.hpp:52, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/adapter/fused.hpp:17, from /usr/local/lib/R/library/BH/include/boost/fusion/functional/generation/make_fused.hpp:13, from /usr/local/lib/R/library/BH/include/boost/fusion/include/make_fused.hpp:11, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:28, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33: /usr/local/lib/R/library/BH/include/boost/get_pointer.hpp:48:40: warning: ‘template class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 48 | template T * get_pointer(std::auto_ptr const& p) | ^~~~~~~~ /usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here 59 | template class auto_ptr; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_log.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob.hpp:126, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:16: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_lpdf.hpp: In function ‘stan::return_type_t stan::math::gaussian_dlm_obs_lpdf(const T_y&, const T_F&, const T_G&, const T_V&, const T_W&, const T_m0&, const T_C0&)’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_lpdf.hpp:264: note: ‘-Wmisleading-indentation’ is disabled from this point onwards, since column-tracking was disabled due to the size of the code/headers 264 | if (i == 0) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_lpdf.hpp:264: note: adding ‘-flarge-source-files’ will allow for more column-tracking support, at the expense of compilation time and memory /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:38:0: required from here 38 | Eigen::VectorXd stddev = S_ldlt.vectorD().array().sqrt().matrix(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 5>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:0: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:46:0: required from here 46 | = mu + (S_ldlt.transpositionsP().transpose() * (S_ldlt.matrixL() * z)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gaussian_dlm_obs_rng.hpp:135:0: required from here 135 | Eigen::VectorXd(F.transpose() * theta_t), V_ldlt, rng); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_hidden_state_prob.hpp:77:0: required from here 77 | alphas.col(n) = alphas.col(n).cwiseProduct(beta); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/hmm_latent_rng.hpp:71:0: required from here 71 | probs_vec = alphas.col(n_transitions) / alphas.col(n_transitions).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:0: required from here 49 | return L_S.template triangularView() * B.transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:0: required from here 49 | return L_S.template triangularView() * B.transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::TriangularView >, 2>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::TriangularView >, 2>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::TriangularView >, 2>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::TriangularView >, 2>, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:25:0: required from here 25 | S_inv = ldlt_of_S.solve(S_inv); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:0: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:0: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_wishart_rng.hpp:27:0: required from here 27 | return 0.5 * (asym.transpose() + asym); // ensure symmetry /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:0: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:89:0: required from here 89 | = Sigma_ldlt.vectorD().array().inverse().sqrt().matrix(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:109:0: required from here 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Matrix >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:0: recursively required by substitution of ‘template const Eigen::internal::triangular_solve_retval >, 6>, Other> Eigen::TriangularViewImpl >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase&) const [with int Side = ; Other = ]’ 108 | * (D_ldlt.matrixU().solve( 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from ‘struct Eigen::internal::accessors_level >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 32 | enum { has_direct_access = (traits::Flags & DirectAccessBit) ? 1 : 0, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:0: required from here 110 | .transpose() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:0: required from here 110 | .transpose() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:0: required from here 110 | .transpose() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:0: required from here 111 | * D_ldlt.transpositionsP()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:0: required from here 111 | * D_ldlt.transpositionsP()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/multinomial_logit_lpmf.hpp:39:0: required from here 39 | lp += lgamma(1 + ns_map.sum()) - lgamma(1 + ns_map).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp: In member function ‘virtual std::vector > stan::io::dump::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 694 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 707 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here 102 | if (C_adj.size() > 0) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here 111 | = D_adj.adjoint().template triangularView(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1, -1, false>, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here 116 | D_adj.diagonal() *= 0.5; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from ‘class Eigen::RefBase, 0, Eigen::OuterStride<> > >’ 59 | template class RefBase | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from ‘class Eigen::Ref, 0, Eigen::OuterStride<> >’ 281 | template class Ref | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from ‘class Eigen::LLT, 0, Eigen::OuterStride<> >, 1>’ 76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:142:0: required from here 142 | check_pos_definite("cholesky_decompose", "m", L_factor); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here 144 | L_A.template triangularView().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_factor_constrain.hpp:42:0: required from here 42 | y_val.row(m).head(m) = x.val().segment(pos, m); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:28:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() 28 | * arena_L_val.transpose(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:32:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/gp_exp_quad_cov.hpp:94:0: required from here 94 | adjsigma += (cov_diag.val().array() * cov_diag.adj().array()).sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of ‘template static std::true_type stan::is_base_pointer_convertible >::f(const Eigen::EigenBase*) [with OtherDerived = ]’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible >’ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from ‘struct stan::is_eigen >’ 21 | : bool_constant::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of ‘template class stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix]’ 301 | (is_eigen::value || is_kernel_expression_and_not_scalar::value) /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of ‘class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from ‘class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > >’ 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 0>’ 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from ‘class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 1>’ 148 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 222 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from ‘class stan::math::arena_matrix, void>’ 129 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from ‘class stan::math::vari_value, void>’ 814 | using InnerIterator = typename arena_matrix::InnerIterator; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from ‘const auto& stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 419 | inline const auto& val() const noexcept { return vi_->val(); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from ‘class Eigen::Tridiagonalization >’ 97 | >::type SubDiagonalReturnType; | ^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from ‘class Eigen::SelfAdjointEigenSolver >’ 111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType; | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here 40 | arena_t eigenvals = solver.eigenvalues(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here 27 | g = x.adj(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:170 = Eigen::Diagonal, 0>]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0> > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:49:0: required from here 49 | var log_det = sum(log(M_ldlt.vectorD())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_determinant_spd.hpp:51:0: required from here 51 | reverse_pass_callback([arena_M, log_det, arena_M_inv_transpose]() mutable { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:73:0: required from here 73 | vector_d diff = (x_d.array() - x_d.maxCoeff()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here 81 | Eigen::Map(softmax_x_d_array, a_size) = softmax_x_d.array() / sum; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:50:0: required from here 50 | arena_powers[0] = Eigen::MatrixXd::Identity(N, N); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:53:0: required from here 53 | arena_powers[i] = arena_powers[1] * arena_powers[i - 1]; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:63:0: required from here 63 | adj_M += adj_C * arena_powers[i - 1].transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/matrix_power.hpp:64:0: required from here 64 | adj_C = M_val.transpose() * adj_C; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here 67 | Eigen::Map(variRefB_, M_, N_).adj() += adjB; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from here 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:55:0: required from here 55 | L.col(0).tail(pull) = CPCs.val().head(pull); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:56:0: required from here 56 | arena_acc.tail(pull) = 1.0 - CPCs.val().head(pull).array().square(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:63:0: required from here 63 | L.col(i).tail(pull) = cpc_seg * arena_acc.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:86:0: required from here 86 | -= 2.0 * acc_adj.tail(pull) * acc_val.tail(pull) * cpc_seg_val; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Block, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_corr_L.hpp:90:0: required from here 90 | += L_res.adj().array().col(i).tail(pull) * acc_val.tail(pull).sqrt(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/read_cov_matrix.hpp:56:0: required from here 56 | sds.adj() += (prod.adj().cwiseProduct(corr_L.val())).rowwise().sum(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/rows_dot_self.hpp:41:0: required from here 41 | x.adj() += (2 * res.adj()).asDiagonal() * x.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0, Eigen::Stride<0, 0> >, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here 56 | arena_Fp.diagonal().setZero(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Transpose > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:69:0: required from here 69 | * (arena_Fp.array() * (UUadjT - UUadjT.transpose()).array()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here 70 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from ‘struct Eigen::internal::traits, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 278 | typedef typename DiagonalVectorType::Scalar Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from ‘struct Eigen::EigenBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from ‘class Eigen::DiagonalBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 18 | class DiagonalBase : public EigenBase | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from ‘class Eigen::DiagonalWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 293 | class DiagonalWrapper | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:63:0: required from here 63 | + arena_U * arena_D.asDiagonal().inverse() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:79:0: required from here 79 | vector_d di = 2 * adj_ * (v1_map.val() - v2_map.val()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here 80 | v1_map.adj() += di; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:23:0: required from here 23 | vector_d dtrs_vals = dtrs_map.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1> >::val_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here 26 | fx = fx_var.val(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&):: [with auto:12 = const Eigen::Matrix, -1, 1>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::; Args = {const Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from ‘auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]’ 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/algebra_solver_fp.hpp:101:0: required from here 101 | y_dummy(stan::math::value_of(y)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/solve_powell.hpp:369:0: required from here 369 | Eigen::VectorXd eta = -Jf_x_T_lu_ptr->solve(ret.adj().eval()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here 604 | f_y_t_vars.adj() = -Eigen::Map(NV_DATA_S(yB), N_); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/finite_diff_hessian_times_vector_auto.hpp:62:0: required from here 62 | hvp = (grad_forward - grad_backward) / (2 * epsilon); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/initialize.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:49: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function ‘virtual std::vector > stan::io::random_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 111 | for (comp_iter = 0, real_iter = 0; real_iter < val_r.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:182:0: required from here 182 | return normal_fullrank(Eigen::VectorXd(mu_.array().square()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:183:0: required from here 183 | Eigen::MatrixXd(L_chol_.array().square())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:197:0: required from here 197 | return normal_fullrank(Eigen::VectorXd(mu_.array().sqrt()), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:198:0: required from here 198 | Eigen::MatrixXd(L_chol_.array().sqrt())); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:263:0: required from here 263 | L_chol_.array() /= rhs.L_chol().array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:459:0: required from here 459 | L_grad.diagonal().array() += L_chol_.diagonal().array().inverse(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:314:0: required from here 314 | return eta.array().cwiseProduct(omega_.array().exp()) + mu_.array(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:370:0: required from here 370 | omega_grad.array() += tmp_mu_grad.array().cwiseProduct(eta.array()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_meanfield.hpp:388:0: required from here 388 | omega_grad.array() = omega_grad.array().cwiseProduct(omega_.array().exp()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/nuts/base_nuts.hpp:175:0: required from here 175 | rho = rho_bck + rho_fwd; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, const Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from here 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 2>, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 2>, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 2>, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from ‘class Eigen::SolveImpl >, 2>, Eigen::Matrix, Eigen::Dense>’ 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from ‘class Eigen::Solve >, 2>, Eigen::Matrix >’ 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:53:0: required from here 53 | z.p = z.inv_e_metric_.llt().matrixU().solve(u); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from ‘auto stan::math::to_matrix(const std::vector&, int, int) [with T = double]’ 133 | return Eigen::Map>( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 134 | &x[0], m, n); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/read_dense_inv_metric.hpp:33:0: required from here 33 | inv_metric = stan::math::to_matrix(dense_vals, num_params, num_params); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here 27 | covar = (n / (n + 5.0)) * covar /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:29:0: required from here 29 | * Eigen::MatrixXd::Identity(covar.rows(), covar.cols()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of ‘template typename Eigen::ScalarBinaryOpTraits::Scalar, Eigen::internal::scalar_product_op::Scalar> >::ReturnType Eigen::MatrixBase >::dot(const Eigen::MatrixBase&) const [with OtherDerived = ]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here 27 | var = (n / (n + 5.0)) * var /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:28:0: required from here 28 | + 1e-3 * (5.0 / (n + 5.0)) * Eigen::VectorXd::Ones(var.size()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:68: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function ‘virtual std::vector > stan::io::array_var_context::vals_c(const std::string&) const’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 304 | for (comp_iter = 0, real_iter = 0; real_iter < val_r->second.first.size(); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 317 | real_iter < val_i->second.first.size(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>’ 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::Stride<0, 0> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from ‘class stan::math::arena_matrix, void>’ 13 | class arena_matrix> /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue_varmat.hpp:145:0: required from here 145 | x_ret_vals.coeffRef(j) = x.val().coeff(row_idx_val, col_idx_vals[j]); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_header.hpp:11, from stanExports_gMAP.h:20: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp: At global scope: /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:159: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(std::vector, std::allocator > >&, std::vector&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 159 | inline math::var log_prob(std::vector& theta, stanExports_gMAP.h:1642: note: by ‘model_gMAP_namespace::model_gMAP::log_prob’ 1642 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:154: warning: ‘double stan::model::model_base_crtp::log_prob(std::vector&, std::vector&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 154 | inline double log_prob(std::vector& theta, std::vector& theta_i, stanExports_gMAP.h:1642: note: by ‘model_gMAP_namespace::model_gMAP::log_prob’ 1642 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:96: warning: ‘stan::math::var stan::model::model_base_crtp::log_prob(Eigen::Matrix, -1, 1>&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; stan::math::var = stan::math::var_value; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 96 | inline math::var log_prob(Eigen::Matrix& theta, stanExports_gMAP.h:1642: note: by ‘model_gMAP_namespace::model_gMAP::log_prob’ 1642 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:91: warning: ‘double stan::model::model_base_crtp::log_prob(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ was hidden [-Woverloaded-virtual=] 91 | inline double log_prob(Eigen::VectorXd& theta, stanExports_gMAP.h:1642: note: by ‘model_gMAP_namespace::model_gMAP::log_prob’ 1642 | log_prob(std::vector& params_r, std::vector& params_i, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_gMAP.h:1239:0: required from here 1239 | stan::math::add( 1240 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 1241 | stan::model::index_uni(1)), 1242 | stan::math::elt_multiply( 1243 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 1244 | stan::model::index_uni(2)), beta_raw)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:77:22: required from ‘auto stan::math::add(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 77 | return (c + m.array()).matrix(); | ~~~~~~~^~ stanExports_gMAP.h:1256:0: required from here 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:77:13: required from ‘auto stan::math::add(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 77 | return (c + m.array()).matrix(); | ~~~^~~~~~~~~~~~ stanExports_gMAP.h:1256:0: required from here 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:77:32: required from ‘auto stan::math::add(Scal, const Mat&) [with Scal = double; Mat = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 77 | return (c + m.array()).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_gMAP.h:1256:0: required from here 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:44: required from ‘stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&):: [with auto:216 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:62:46: required from ‘auto stan::math::exp(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_container_st* = 0]’ 62 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1255:0: required from here 1255 | stan::math::exp( 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&):: [with auto:216 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >]’ 47 | f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:62:46: required from ‘auto stan::math::exp(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_container_st* = 0]’ 62 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1255:0: required from here 1255 | stan::math::exp( 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from ‘stan::math::apply_vector_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >, void>::apply, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&):: >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&, const stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&)::&):: [with auto:7 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >, void>::apply, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&):: >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&, const stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >]’ 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:62:46: required from ‘auto stan::math::exp(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; stan::require_container_st* = 0]’ 62 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1255:0: required from here 1255 | stan::math::exp( 1256 | stan::math::add( 1257 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1258 | stan::model::index_uni(1)), 1259 | stan::math::multiply( 1260 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 1261 | stan::model::index_uni(2)), tau_raw))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from ‘stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&):: [with auto:703 = Eigen::Matrix]’ 158 | return plain_type_t::NullaryExpr( 159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) { 160 | math::check_range("vector[multi] indexing", name, v_ref.size(), 161 | idx.ns_[i]); 162 | return v_ref.coeff(idx.ns_[i] - 1); 163 | }); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&)::; Args = {Eigen::Matrix&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:156:0: required from ‘auto stan::model::rvalue(EigVec&&, const char*, const index_multi&) [with EigVec = Eigen::Matrix&; stan::require_eigen_vector_t* = 0]’ 156 | return stan::math::make_holder( 157 | [name, &idx](auto& v_ref) { 158 | return plain_type_t::NullaryExpr( 159 | idx.ns_.size(), [name, &idx, &v_ref](Eigen::Index i) { 160 | math::check_range("vector[multi] indexing", name, v_ref.size(), 161 | idx.ns_[i]); 162 | return v_ref.coeff(idx.ns_[i] - 1); 163 | }); 164 | }, 165 | stan::math::to_ref(v)); stanExports_gMAP.h:1266:0: required from here 1266 | stan::model::rvalue(tau, "tau", 1267 | stan::model::index_multi(tau_strata_gindex)), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from ‘auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]’ 107 | return m1 * m2; | ~~~^~~~ stanExports_gMAP.h:1287:0: required from here 1287 | stan::math::add(stan::math::multiply(X_param, beta), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Mat2 = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_gMAP.h:1287:0: required from here 1287 | stan::math::add(stan::math::multiply(X_param, beta), 1288 | stan::model::rvalue(eta, "eta", 1289 | stan::model::index_multi(group_index))), /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from ‘struct Eigen::internal::traits >’ 17 | struct traits > : traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:11: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar&>(const std::vector&)::; Args = {const std::vector >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:72:21: required from ‘auto stan::math::as_array_or_scalar(T&&) [with T = const std::vector&; stan::require_std_vector_t* = 0; stan::require_not_std_vector_t::type>* = 0]’ 72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | std::forward(v)); | ~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:28:39: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 28 | ArrayAT a_array = as_array_or_scalar(a); | ~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from ‘struct Eigen::internal::traits, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > > >’ 38 | >::type Scalar; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:43: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from ‘class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >’ 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:55: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from ‘stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&):: [with auto:10 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&)::; T2 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_t::type> >* = 0; T = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from ‘auto stan::math::fabs(const Container&) [with Container = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_container_st* = 0]’ 66 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:47:37: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&)::; T2 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_t::type> >* = 0; T = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]’ 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from ‘auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_container_st* = 0]’ 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:49:25: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk)); | ~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from ‘struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>’ 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from ‘auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]’ 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from ‘stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/lmgamma.hpp:16:0: required from here 16 | : op_dv_vari(lmgamma(a, bvi->val_), a, bvi) {} /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from ‘class Eigen::Array’ 45 | class Array | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Array >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from ‘Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]’ 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:22: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long unsigned int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here 97 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: ‘int’ and ‘std::vector >::size_type’ {aka ‘long unsigned int’} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from ‘stan::math::value_of_rec, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&):: [with auto:2 = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of_rec, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::; Args = {Eigen::Map, 0, Eigen::Stride<0, 0> >}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:108:21: required from ‘auto stan::math::value_of_rec(T&&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; = void; = void]’ 108 | return make_holder( | ~~~~~~~~~~~^ 109 | [](auto& m) { | ~~~~~~~~~~~~~ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | }, | ~~ 112 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_greater_or_equal.hpp:157:30: required from ‘void stan::math::check_greater_or_equal(const char*, const char*, const T_y&, const T_low&, Idxs ...) [with T_y = std::vector; T_low = int; stan::require_vector_t* = 0; stan::require_not_std_vector_vt* = 0; stan::require_stan_scalar_t* = 0; Idxs = {}]’ 157 | auto&& y_arr = value_of_rec(as_array_or_scalar(to_ref(y))); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:337:0: required from here 337 | stan::math::check_greater_or_equal(function__, "r", r, 0); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_gMAP.h: In instantiation of ‘void model_gMAP_namespace::model_gMAP::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = std::vector; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_gMAP.h:1670:0: required from here 1670 | unconstrain_array_impl(params_constrained, params_i, 1671 | params_unconstrained, pstream); stanExports_gMAP.h:1356: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 1356 | int pos__ = std::numeric_limits::min(); stanExports_gMAP.h: In instantiation of ‘void model_gMAP_namespace::model_gMAP::unconstrain_array_impl(const VecVar&, const VecI&, VecVar&, std::ostream*) const [with VecVar = Eigen::Matrix; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_gMAP.h:1680:0: required from here 1680 | unconstrain_array_impl(params_constrained, params_i, 1681 | params_unconstrained, pstream); stanExports_gMAP.h:1356: warning: variable ‘pos__’ set but not used [-Wunused-but-set-variable] 1356 | int pos__ = std::numeric_limits::min(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp: In instantiation of ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’: stanExports_gMAP.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1252: warning: variable ‘ret’ set but not used [-Wunused-but-set-variable] 1252 | int ret = stan::services::error_codes::CONFIG; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 181 | Eigen::Matrix a_args(2); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 182 | Eigen::Matrix b_args(1); | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:117:39: required from ‘TupleT stan::math::internal::grad_2F1_impl_ab(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 117 | inner_diff = g_current.array().abs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:204:78: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 204 | grad_tuple_ab = grad_2F1_impl_ab( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 205 | a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/../plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of ‘template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]’ 62 | cast() const | ^~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:12: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:47:0: required from here 47 | stan::math::check_not_nan(function, "Mean vector", mu); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:74:0: required from here 74 | stan::math::check_not_nan(function, "Cholesky factor", L_chol); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:207:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 207 | for (size_t i = 0; i < x.rows(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:208:26: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 208 | for (size_t j = 0; j < x.cols(); j++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:21:0: required from here 21 | stan::math::check_finite("check_finite", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_diag_inv_metric.hpp:22:0: required from here 22 | stan::math::check_positive("check_positive", "inv_metric", inv_metric); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from ‘bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]’ 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from ‘bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]’ 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here 30 | if (!var.allFinite()) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta.hpp:70, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/core.hpp:4, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:10: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp: In instantiation of ‘void stan::math::check_less_or_equal(const char*, const char*, const T_y&, const T_high&, Idxs ...) [with T_y = long unsigned int; T_high = long int; stan::require_all_stan_scalar_t* = 0; Idxs = {}]’: /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from ‘std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long int]’ 79 | stan::math::check_less_or_equal("validate_dims", "array_var_context", 80 | elem_dims_total[dims.size()], array_size); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_less_or_equal.hpp:39:20: warning: comparison of integer expressions of different signedness: ‘const long unsigned int’ and ‘const long int’ [-Wsign-compare] 39 | if (unlikely(!(y <= high))) { | ~~~^~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/compiler_attributes.hpp:9:41: note: in definition of macro ‘unlikely’ 9 | #define unlikely(x) __builtin_expect(!!(x), 0) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp: In instantiation of ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; Eigen::MatrixXd = Eigen::Matrix]’: /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_gMAP.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: ‘std::vector >::size_type’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 55 | if (p_names.size() != draws.cols()) { /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:71: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::Index’ {aka ‘long int’} [-Wsign-compare] 71 | for (size_t i = 0; i < draws.rows(); ++i) { In file included from /usr/local/lib/R/library/BH/include/boost/concept/assert.hpp:35, from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:19, from /usr/local/lib/R/library/BH/include/boost/range/size_type.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range/size.hpp:21, from /usr/local/lib/R/library/BH/include/boost/range/functions.hpp:20, from /usr/local/lib/R/library/BH/include/boost/range.hpp:18, from /usr/local/lib/R/library/BH/include/boost/numeric/odeint/util/resize.hpp:22: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept >, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:26, from /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:16, from /usr/local/lib/R/library/BH/include/boost/algorithm/string.hpp:23, from /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4, from /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:46: /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::token_finderF >; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:98:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function ‘void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 40 | void constraints() /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FormatterConcept >, boost::algorithm::detail::first_finderF, __gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_format.hpp:103:0: required from ‘void boost::algorithm::find_format(SequenceT&, FinderT, FormatterT) [with SequenceT = std::__cxx11::basic_string; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/replace.hpp:179:0: required from ‘void boost::algorithm::replace_first(SequenceT&, const Range1T&, const Range2T&) [with SequenceT = std::__cxx11::basic_string; Range1T = char [11]; Range2T = char [1]]’ 179 | ::boost::algorithm::find_format( 180 | Input, 181 | ::boost::algorithm::first_finder(Search), 182 | ::boost::algorithm::const_formatter(Format) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:65:52: warning: ‘this’ pointer is null [-Wnonnull] 65 | static void failed() { ((Model*)0)->constraints(); } | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function ‘void boost::algorithm::FormatterConcept::constraints() [with FormatterT = boost::algorithm::detail::const_formatF >; FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]’ 65 | void constraints() /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:19: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_gMAP.h: In instantiation of ‘void model_gMAP_namespace::model_gMAP::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_gMAP.h:1633:0: required from ‘void model_gMAP_namespace::model_gMAP::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 1633 | write_array_impl(base_rng, params_r, params_i, vars, 1634 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_gMAP.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) stanExports_gMAP.h:1191: warning: unused variable ‘jacobian__’ [-Wunused-variable] 1191 | constexpr bool jacobian__ = false; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from ‘stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]’ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from ‘static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]’ 93 | return f(x); | ~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:83:39: required from ‘auto stan::math::log_sum_exp(const T&) [with T = Eigen::Matrix; stan::require_container_st* = 0]’ 83 | return apply_vector_unary::reduce(x, [&](const auto& v) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ 84 | if (v.size() == 0) { | ~~~~~~~~~~~~~~~~~~~~ 85 | return NEGATIVE_INFTY; | ~~~~~~~~~~~~~~~~~~~~~~ 86 | } | ~ 87 | const auto& v_ref = to_ref(v); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 88 | const double max = v_ref.maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 89 | if (!std::isfinite(max)) { | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 90 | return max; | ~~~~~~~~~~~ 91 | } | ~ 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/dirichlet_rng.hpp:59:35: required from here 59 | double log_sum_y = log_sum_exp(log_y); | ~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:330: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 72 | typedef blas_data_mapper ResMapper; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘class Eigen::internal::gebp_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from ‘struct Eigen::internal::gebp_kernel, 4, 4, false, false>’ 1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 92 | gebp_kernel gebp; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:384:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 384 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]’ 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:25:0: required from here 25 | vector_d diff = dtrs_vals.array() - dtrs_vals.mean(); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, -1>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 451 | subdiag = mat.template diagonal<-1>().real(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from ‘class Eigen::VectorBlock, 1, -1, false>, -1>’ 56 | template class VectorBlock | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Matrix >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 191 | _pk.noalias() = -_gk; /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 31 | using ret_type = return_var_matrix_t; stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:35:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 35 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2.val())); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:35:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 35 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2.val())); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:39:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 39 | const auto ret_adj = ret.adj().coeffRef(i, j); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:49:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 49 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2)); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:51:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array(); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:51:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array(); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:51:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array(); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:57:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 57 | arena_t ret(arena_m1.cwiseProduct(arena_m2.val())); stanExports_gMAP.h:952:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:152:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 152 | [ret, arena_a]() mutable { arena_a.adj() += ret.adj_op(); }); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Matrix; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:949:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 949 | stan::math::add( 950 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 951 | stan::model::index_uni(1)), 952 | stan::math::elt_multiply( 953 | stan::model::rvalue(beta_raw_guess, "beta_raw_guess", 954 | stan::model::index_uni(2)), beta_raw)), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:145:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 145 | arena_t res = arena_A.val() * arena_B.val().array(); stanExports_gMAP.h:969:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:163:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 163 | arena_B.adj().array() += arena_A * res.adj().array(); stanExports_gMAP.h:969:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:170:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 170 | arena_t res = arena_A.val() * arena_B.array(); stanExports_gMAP.h:969:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:172:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = double; T2 = Eigen::Matrix, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 172 | arena_A.adj() += (res.adj().array() * arena_B.array()).sum(); stanExports_gMAP.h:969:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:966:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 966 | stan::math::add( 967 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 968 | stan::model::index_uni(1)), 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:966:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 966 | stan::math::add( 967 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 968 | stan::model::index_uni(1)), 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = double; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:966:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 966 | stan::math::add( 967 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 968 | stan::model::index_uni(1)), 969 | stan::math::multiply( 970 | stan::model::rvalue(tau_raw_guess, "tau_raw_guess", 971 | stan::model::index_uni(2)), tau_raw))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/elt_multiply.hpp:31:0: required from ‘auto stan::math::elt_multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix, -1, 1>; Mat2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]’ 31 | using ret_type = return_var_matrix_t; stanExports_gMAP.h:982:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 982 | stan::model::assign(eta, stan::math::elt_multiply(xi_eta, tau_group), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:34:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 34 | auto arena_A_val = to_arena(arena_A.val()); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 36 | using return_t stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 47 | arena_A.adj() += res_adj * arena_B_val.transpose(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&):: [with auto:12 = stan::math::arena_matrix, -1, -1>, void>]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 66 | = return_var_matrix_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1> >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 65 | using return_t stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:113:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; stan::require_all_rev_matrix_t* = 0]’ 113 | using op_ret_type = decltype(a.val() + b.val()); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), 998 | stan::model::rvalue(eta, "eta", 999 | stan::model::index_multi(group_index))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from ‘struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1, 0, -1, 1> > > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1, 0, -1, 1> > >’ 80 | : bool_constant...>::value> {}; | ^~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1, 0, -1, 1> >}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:114:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; stan::require_all_rev_matrix_t* = 0]’ 114 | using ret_type = return_var_matrix_t; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), 998 | stan::model::rvalue(eta, "eta", 999 | stan::model::index_multi(group_index))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:117:0: required from ‘auto stan::math::add(const VarMat1&, const VarMat2&) [with VarMat1 = Eigen::Matrix, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; stan::require_all_rev_matrix_t* = 0]’ 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), 998 | stan::model::rvalue(eta, "eta", 999 | stan::model::index_multi(group_index))), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:131:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 131 | arena_t> res = inv_c * arena_m.val(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:134:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 134 | arena_c.adj() -= (inv_times_adj * res.val().array()).sum(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:143:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 143 | arena_m.adj().array() += inv_c * res.adj_op().array(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:143:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 143 | arena_m.adj().array() += inv_c * res.adj_op().array(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:149:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 149 | arena_t> res = inv_c * value_of(m).array(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:149:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 149 | arena_t> res = inv_c * value_of(m).array(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_division.hpp:151:0: required from ‘auto stan::math::divide(const Mat&, Scalar) [with Scalar = double; Mat = Eigen::Matrix, -1, 1>; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_st_var_or_arithmetic* = 0; stan::require_any_st_var* = 0]’ 151 | arena_c.adj() -= inv_c * (res.adj().array() * res.val().array()).sum(); stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:14 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:1156:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:147:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:1156:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from ‘struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of ‘template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]’ 23 | is_any_var_matrix::value, /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:148:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 148 | using ret_type = return_var_matrix_t; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:1156:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:150:0: required from ‘auto stan::math::add(const VarMat&, const Arith&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/operator_addition.hpp:169:0: required from ‘auto stan::math::add(const Arith&, const VarMat&) [with Arith = Eigen::Map, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]’ 169 | return add(b, a); stanExports_gMAP.h:1156:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 35 | check_finite("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 36 | check_finite("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 39 | check_not_nan("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Matrix]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from ‘stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]’ 40 | check_not_nan("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from ‘stan::return_type_t stan::math::hypergeometric_2F1(const Ta1&, const Ta2&, const Tb&, const Tz&) [with Ta1 = double; Ta2 = double; Tb = double; Tz = double; ScalarT = double; OptT = boost::optional; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]’ 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:190:39: required from ‘TupleT stan::math::internal::grad_2F1_impl(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool calc_a1 = true; bool calc_a2 = true; bool calc_b1 = true; bool calc_z = true; T1 = double; T2 = double; T3 = double; T_z = double; ScalarT = double; TupleT = std::tuple]’ 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_2F1.hpp:306:57: required from ‘auto stan::math::grad_2F1(const T1&, const T2&, const T3&, const T_z&, double, int) [with bool ReturnSameT = true; T1 = double; T2 = double; T3 = double; T_z = double; stan::require_t >* = 0]’ 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ In file included from /usr/local/lib/R/library/BH/include/boost/math/special_functions/beta.hpp:1721, from /usr/local/lib/R/library/BH/include/boost/math/special_functions/binomial.hpp:15, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/choose.hpp:7, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun.hpp:46, from /usr/local/lib/R/library/StanHeaders/include/stan/math/prim.hpp:14: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp: In instantiation of ‘boost::math::detail::temme_root_finder::temme_root_finder(T, T) [with T = double]’: /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:304:7: required from ‘T boost::math::detail::temme_method_2_ibeta_inverse(T, T, T, T, T, const Policy&) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 304 | temme_root_finder(-lu, alpha), x, lower, upper, policies::digits() / 2); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:615:48: required from ‘T boost::math::detail::ibeta_inv_imp(T, T, T, T, const Policy&, T*) [with T = double; Policy = boost::math::policies::policy, boost::math::policies::promote_float, boost::math::policies::promote_double, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy, boost::math::policies::default_policy>]’ 615 | x = temme_method_2_ibeta_inverse(a, b, p, r, theta, pol); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:992:30: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(T1, T2, T3, T4*, const Policy&) [with T1 = double; T2 = double; T3 = double; T4 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 992 | rx = detail::ibeta_inv_imp( | ~~~~~~~~~~~~~~~~~~~~~^ 993 | static_cast(a), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 994 | static_cast(b), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 995 | static_cast(p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 996 | static_cast(1 - p), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 997 | forwarding_policy(), &ry); | ~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:1023:20: required from ‘boost::math::tools::promote_args_t boost::math::ibeta_inv(RT1, RT2, RT3, const Policy&) [with RT1 = double; RT2 = double; RT3 = double; Policy = policies::policy, policies::pole_error, policies::promote_double, policies::digits2<0>, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy, policies::default_policy>; tools::promote_args_t = double]’ 1023 | return ibeta_inv(a, b, p, static_cast(nullptr), pol); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv_inc_beta.hpp:32:32: required from here 32 | return boost::math::ibeta_inv(a, b, p, boost_policy_t<>()); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/math/special_functions/detail/ibeta_inverse.hpp:29:15: warning: unused variable ‘x_extrema’ [-Wunused-variable] 29 | const T x_extrema = 1 / (1 + a); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 1>; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 2, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 2, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 2, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 2, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 2, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 2, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 203 | PanelType panel(m_arg, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:277: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 2, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 2, -1, true> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from ‘PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long int]’ 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 100 | pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, size); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 106 | pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2256:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2256 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2258:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2258 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2259 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2259:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2298 | PacketBlock kernel_half; | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2298:39: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2304 | PacketBlock kernel_quarter; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2304:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gebp_kernel::operator()(const DataMapper&, const LhsScalar*, const RhsScalar*, Index, Index, Index, ResScalar, Index, Index, Index, Index) [with LhsScalar = double; RhsScalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 113 | gebp(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | (std::min)(size,i2), alpha, -1, -1, 0, 0); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1920:103: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1920 | const int SResPacketHalfSize = unpacket_traits::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1921 | const int SResPacketQuarterSize = unpacket_traits::half>::half>::size; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1921:138: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1977:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1977 | typedef typename conditional=8,typename unpacket_traits::half,SResPacket>::type SResPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1978:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1978 | typedef typename conditional=8,typename unpacket_traits::half,SLhsPacket>::type SLhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1979:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1979 | typedef typename conditional=8,typename unpacket_traits::half,SRhsPacket>::type SRhsPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1980:135: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 1980 | typedef typename conditional=8,typename unpacket_traits::half,SAccPacket>::type SAccPacketHalf; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from ‘void Eigen::internal::tribb_kernel::operator()(ResScalar*, Index, Index, const LhsScalar*, const RhsScalar*, Index, Index, const ResScalar&) [with LhsScalar = double; RhsScalar = double; Index = long int; int mr = 4; int nr = 4; bool ConjLhs = false; bool ConjRhs = false; int ResInnerStride = 1; int UpLo = 2; ResScalar = double]’ 155 | Matrix buffer((internal::constructor_without_unaligned_array_assert())); | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:26: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:43: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:352:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 352 | Block A21(mat,k+1,k,rs,1); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:80: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:358:67: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, 6>’ 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:35: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, true>, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, false> > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, -1, 1, false> >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:32: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from ‘auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix; T2 = double; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from ‘class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from ‘auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix; T2 = double; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_gMAP.h:1028:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from ‘auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]’ 45 | return m1 + m2; | ~~~^~~~ stanExports_gMAP.h:1156:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_linesearch.hpp:247:0: required from ‘int stan::optimization::WolfeLineSearch(FunctorType&, Scalar&, XType&, Scalar&, XType&, const XType&, const XType&, const Scalar&, const XType&, const Scalar&, const Scalar&, const Scalar&, const Scalar&, const Scalar&) [with FunctorType = ModelAdaptor; Scalar = double; XType = Eigen::Matrix]’ 247 | x1.noalias() = x0 + alpha1 * p; /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 209 | = WolfeLineSearch(_func, _alpha, _xk_1, _fk_1, _gk_1, _pk, _xk, _fk, 210 | _gk, _ls_opts.c1, _ls_opts.c2, _ls_opts.minAlpha, 211 | _ls_opts.maxLSIts, _ls_opts.maxLSRestarts); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from ‘void stan::optimization::BFGSUpdate_HInv::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 55 | pk.noalias() = -(_Hk * gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 254 | _qn.search_direction(_pk, _gk); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from ‘stan::math::value_of, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&):: [with auto:12 = Eigen::ArrayWrapper, -1, 1> >]’ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:58:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 58 | decltype(auto) y_val = to_ref(as_value_column_array_or_scalar(y_ref)); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | = to_ref_if::value>(y_scaled * y_scaled); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 102 | square_y_scaled / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:104:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 104 | log1p(square_y_scaled_over_nu)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:147:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 147 | partials<3>(ops_partials) = rep_deriv / sigma_val; stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv >(const Eigen::Array&):: [with auto:221 = Eigen::Array]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:76:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 76 | = to_ref_if::value>(inv(sigma_val)); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log >(const Eigen::Array&):: [with auto:170 = Eigen::Array]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 102 | square_y_scaled / nu_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square >(const Eigen::Array&):: [with auto:239 = Eigen::Array]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:121:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 121 | const auto& square_sigma = square(sigma_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:147:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 147 | partials<3>(ops_partials) = rep_deriv / sigma_val; stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv > >(const Eigen::ArrayWrapper >&):: [with auto:221 = Eigen::ArrayWrapper >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:76:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 76 | = to_ref_if::value>(inv(sigma_val)); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log > >(const Eigen::ArrayWrapper >&):: [with auto:170 = Eigen::ArrayWrapper >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1066:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1066 | lp_accum__.add(stan::math::normal_lpdf(tau, 0, 1067 | stan::model::rvalue(tau_prior_stan, 1068 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 85 | logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >&):: [with auto:170 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 85 | logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >&):: [with auto:221 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:93:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 93 | inv(beta_val - alpha_val)); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 97 | partials<2>(ops_partials) = -inv_beta_minus_alpha * math::size(y); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:97:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 97 | partials<2>(ops_partials) = -inv_beta_minus_alpha * math::size(y); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 105 | partials<1>(ops_partials) = inv_beta_minus_alpha * math::size(y); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 94 | logp = -sum(lgamma(alpha_val)) * N / math::size(alpha); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 106 | logp += sum((alpha_val - 1.0) * log_y) * N / max_size(alpha, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:92:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 92 | partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:92:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 92 | partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | logp -= sum((alpha_val + 1.0) * log_y) * N / max_size(y, alpha); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | logp -= sum((alpha_val + 1.0) * log_y) * N / max_size(y, alpha); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::ArrayWrapper > > >(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&):: [with auto:239 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:67:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 67 | square(inv_sigma)); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:74:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 74 | = N * NEG_LOG_SQRT_TWO_PI - 0.5 * sum(square(logy_m_mu) * inv_sigma_sq); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:81:39: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 81 | logp -= sum(log1p(square(y_minus_mu * inv_sigma))); | ~~~~~~~~~~~^~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:81:27: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 81 | logp -= sum(log1p(square(y_minus_mu * inv_sigma))); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:81:20: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 81 | logp -= sum(log1p(square(y_minus_mu * inv_sigma))); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:13: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~^~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:43: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:26: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:100:39: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 100 | partials<0>(ops_partials) = -mu_deriv; | ^~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:110:55: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:111:35: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | * inv_sigma | ^~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:112:35: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | * inv_sigma | ~~~~~~~~~~~ 112 | / (sigma_squared + y_minus_mu_squared); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/exponential_lpdf.hpp:92:35: required from ‘stan::return_type_t stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 92 | partials<0>(ops_partials) = -forward_as(beta_val); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1127:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1127 | lp_accum__.add(stan::math::exponential_lpdf(tau, 1128 | stan::model::rvalue(tau_prior_stan, 1129 | "tau_prior_stan", stan::model::index_uni(1)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/exponential_lpdf.hpp:100:47: required from ‘stan::return_type_t stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 100 | partials<1>(ops_partials) = inv(beta_val) - y_val; | ~~~~~~~~~~~~~~^~~~~~~ stanExports_gMAP.h:1127:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1127 | lp_accum__.add(stan::math::exponential_lpdf(tau, 1128 | stan::model::rvalue(tau_prior_stan, 1129 | "tau_prior_stan", stan::model::index_uni(1)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from ‘stan::math::inv, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: [with auto:221 = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:76:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 76 | = to_ref_if::value>(inv(sigma_val)); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: [with auto:170 = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::Array]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:70:61: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 70 | = to_ref_if::value>(inv_logit(alpha_val)); | ~~~~~~~~~^~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::Array >&)::, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::Array >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:72:61: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 72 | = to_ref_if::value>(inv_logit(-alpha_val)); | ~~~~~~~~~^~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_binary.hpp:60:34: required from ‘stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&):: [with auto:60 = stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; auto:61 = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; auto:62 = const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 60 | return x_inner.binaryExpr(y_inner, f_inner); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:80:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 80 | logp += sum(binomial_coefficient_log(N_val, n_val)) * maximum_size | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from ‘class stan::math::Holder, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >’ 115 | class Holder | ^~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:312:16: required from ‘auto stan::math::internal::make_holder_impl_construct_object(T&&, std::index_sequence, const std::tuple&) [with T = Eigen::CwiseBinaryOp, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; long unsigned int ...Is = {0}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::}; std::index_sequence = std::integer_sequence]’ 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from ‘auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::apply_scalar_binary, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::&&)::; long unsigned int ...Is = {0, 1, 2}; Args = {stan::math::binomial_coefficient_log, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&}; std::index_sequence = std::integer_sequence]’ 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:80:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 80 | logp += sum(binomial_coefficient_log(N_val, n_val)) * maximum_size | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Array >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:50: required from ‘stan::math::exp >(const Eigen::Array&):: [with auto:216 = Eigen::Array]’ 63 | x, [](const auto& v) { return v.array().exp(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:72:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector; T_log_rate = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 72 | = to_ref_if::value>(exp(alpha_val)); stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:79:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector; T_log_rate = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | logp -= sum(lgamma(n_val + 1.0)) * N / math::size(n); stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:79:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector; T_log_rate = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 79 | logp -= sum(lgamma(n_val + 1.0)) * N / math::size(n); stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:83:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector; T_log_rate = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 83 | partials<0>(ops_partials) = n_val - exp_alpha; stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from ‘Eigen::MapBase::ScalarWithConstIfNotLvalue& Eigen::MapBase::coeffRef(Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long int]’ 15 | EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 367 | matA.col(i).coeffRef(i+1) = 1; | ~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from ‘void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase&, Eigen::DenseBase&, const Eigen::JacobiRotation&) [with VectorX = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]’ 475 | EIGEN_PLAIN_ENUM_MIN(evaluator::Alignment, evaluator::Alignment), | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from ‘void Eigen::MatrixBase::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation&) [with OtherScalar = double; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long int]’ 315 | internal::apply_rotation_in_the_plane(x, y, j.transpose()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:895:24: required from ‘void Eigen::internal::tridiagonal_qr_step(RealScalar*, RealScalar*, Index, Index, Scalar*, Index) [with int StorageOrder = 0; RealScalar = double; Scalar = double; Index = long int]’ 895 | q.applyOnTheRight(k,k+1,rot); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:548:87: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 548 | internal::tridiagonal_qr_step(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, -1, 1, false> >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::min_coeff_visitor, -1, 1, false>, 0>; Derived = Eigen::Block, -1, 1, false>]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:323:14: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 323 | this->visit(minVisitor); | ~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:496:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::minCoeff(IndexType*) const [with IndexType = long int; Derived = Eigen::Block, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]’ 496 | return minCoeff(index); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:563:35: required from ‘Eigen::ComputationInfo Eigen::internal::computeFromTridiagonal_impl(DiagType&, SubDiagType&, Eigen::Index, bool, MatrixType&) [with MatrixType = Eigen::Matrix; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long int]’ 563 | diag.segment(i,n-i).minCoeff(&k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, true>, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:379:74: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from ‘struct Eigen::internal::evaluator_wrapper_base, -1, 1, false> > >’ 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:387:50: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:147:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 147 | partials<3>(ops_partials) = rep_deriv / sigma_val; stanExports_gMAP.h:1012:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1012 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1013 | re_dist_t_df, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&>(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:14 = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&>(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; Args = {const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | const auto& square_y_scaled = square((y_val - mu_val) / sigma_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | square_y_scaled / nu_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:107:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 107 | T_partials_return logp = -sum((half_nu + 0.5) * log1p_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:124:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:125:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 124 | (nu_val + 1) * (y_val - mu_val) 125 | / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val)); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:127:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 127 | partials<0>(ops_partials) = -deriv_y_mu; stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:136:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:137:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 136 | (nu_val + 1) * square_y_scaled_over_nu / (1 + square_y_scaled_over_nu) 137 | - 1); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:144:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:143:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 142 | = 0.5 143 | * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val 144 | + rep_deriv / nu_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:147:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 147 | partials<3>(ops_partials) = rep_deriv / sigma_val; stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = int; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1066:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1066 | lp_accum__.add(stan::math::normal_lpdf(tau, 0, 1067 | stan::model::rvalue(tau_prior_stan, 1068 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | logp -= sum(beta_val * inv_y) * N / max_size(y, beta); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 105 | = (beta_val * inv_y - alpha_val - 1) * inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:108:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 108 | partials<2>(ops_partials) = alpha_val / beta_val - inv_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:74:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 74 | = N * NEG_LOG_SQRT_TWO_PI - 0.5 * sum(square(logy_m_mu) * inv_sigma_sq); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 87 | >= 2>(logy_m_mu * inv_sigma_sq); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:89:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 89 | partials<0>(ops_partials) = -(1 + logy_m_mu_div_sigma) / y_val; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::Array >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma; stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >&)::, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/square.hpp:70:53: required from ‘stan::math::square, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >&):: [with auto:239 = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >]’ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:13: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~^~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:43: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:97:26: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 97 | 2 * y_minus_mu / (sigma_squared + y_minus_mu_squared)); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:100:39: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 100 | partials<0>(ops_partials) = -mu_deriv; | ^~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:110:55: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:111:35: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | * inv_sigma | ^~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/cauchy_lpdf.hpp:112:35: required from ‘stan::return_type_t stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 110 | partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | * inv_sigma | ~~~~~~~~~~~ 112 | / (sigma_squared + y_minus_mu_squared); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1118:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1118 | lp_accum__.add(stan::math::cauchy_lpdf(tau, 1119 | stan::model::rvalue(tau_prior_stan, 1120 | "tau_prior_stan", stan::model::index_uni(1)), 1121 | stan::model::rvalue(tau_prior_stan, 1122 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/exponential_lpdf.hpp:100:47: required from ‘stan::return_type_t stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 100 | partials<1>(ops_partials) = inv(beta_val) - y_val; | ~~~~~~~~~~~~~~^~~~~~~ stanExports_gMAP.h:1127:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1127 | lp_accum__.add(stan::math::exponential_lpdf(tau, 1128 | stan::model::rvalue(tau_prior_stan, 1129 | "tau_prior_stan", stan::model::index_uni(1)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 94 | >= 2>(inv_sigma * y_scaled); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | partials<0>(ops_partials) = -scaled_diff; stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from ‘static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]’ 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >(const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >&):: [with auto:170 = Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from ‘stan::math::log, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >&):: [with auto:170 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >]’ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:77:38: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:50: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:78:32: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 77 | T_partials_return logp = sum(n_val * log_inv_logit_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 78 | + (N_val - n_val) * log_inv_logit_neg_alpha); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:19: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:59: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:88:41: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 88 | = n_val * inv_logit_neg_alpha - (N_val - n_val) * inv_logit_alpha; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:92:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~^~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:94:17: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ^~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, void>::apply(const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >&)::, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:93:11: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | sum_n * inv_logit_neg_alpha | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 93 | - (sum(N_val) * maximum_size / math::size(N) - sum_n) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 94 | * inv_logit_alpha); | ~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from ‘class Eigen::ArrayWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >’ 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from ‘stan::math::as_array_or_scalar, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >&>(const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >&):: [with auto:14 = const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >]’ 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of ‘template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >&>(const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >&)::; Args = {const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >&}; stan::require_plain_type_t()((declval)()...))>* = ]’ 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:21: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::Array > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:83:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = false; T_n = std::vector; T_log_rate = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 83 | partials<0>(ops_partials) = n_val - exp_alpha; stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from ‘stan::math::var stan::math::accumulator::type>::value, void>::type>::sum() const [with T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value; stan::math::var = stan::math::var_value]’ 135 | inline var sum() const { return stan::math::sum(buf_); } stanExports_gMAP.h:1164:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1164 | return lp_accum__.sum(); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from ‘static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 1; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int UpLo = 2; int Version = 0; ResScalar = double]’ 116 | sybb(_res+resStride*i2 + resIncr*i2, resIncr, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha); | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from ‘static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]’ 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | IsRowMajor ? RowMajor : ColMajor, MatrixType::InnerStrideAtCompileTime, UpLo> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 113 | ::run(size, depth, | ~~~~~^~~~~~~~~~~~~ 114 | actualOther.data(), actualOther.outerStride(), actualOther.data(), actualOther.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 115 | mat.data(), mat.innerStride(), mat.outerStride(), actualAlpha, blocking); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from ‘Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]’ 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 453 | RealScalar scale = mat.cwiseAbs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:34:74: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:60: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointRank2Update.h:35:23: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/operands_and_partials.hpp:67:0: required from ‘void stan::math::internal::update_adjoints(Matrix1&, const Matrix2&, const stan::math::var&) [with Matrix1 = stan::math::arena_matrix, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]’ 67 | x.adj().array() += z.adj() * y.array(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/functor/partials_propagator.hpp:91:0: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:105:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 105 | return ops_partials.build(logp); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/student_t_lpdf.hpp:85:0: required from ‘stan::return_type_t stan::math::student_t_lpdf(const T_y&, const T_dof&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_dof = double; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 85 | check_positive_finite(function, "Scale parameter", sigma_val); stanExports_gMAP.h:1036:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1036 | lp_accum__.add(stan::math::student_t_lpdf(xi_eta, 1037 | re_dist_t_df, 1038 | ((stan::model::rvalue(beta, "beta", 1039 | stan::model::index_uni(1)) - 1040 | stan::model::rvalue(beta_raw_guess, 1041 | "beta_raw_guess", stan::model::index_uni(1), 1042 | stan::model::index_uni(1))) / 1043 | stan::model::rvalue(beta_raw_guess, 1044 | "beta_raw_guess", stan::model::index_uni(2), 1045 | stan::model::index_uni(1))), 1046 | stan::math::divide(tau_group, 1047 | stan::model::rvalue(beta_raw_guess, 1048 | "beta_raw_guess", stan::model::index_uni(2), 1049 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 63 | check_finite(function, "Location parameter", mu_val); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive_finite > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive_finite.hpp:24:20: required from ‘void stan::math::check_positive_finite(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:72:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 72 | check_positive_finite(function, "Shape parameter", alpha_val); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_nonnegative >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_nonnegative.hpp:26:20: required from ‘void stan::math::check_nonnegative(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 26 | elementwise_check([](double x) { return x >= 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 27 | "nonnegative"); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:46:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 46 | check_nonnegative(function, "Random variable", y_val); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, 0, Eigen::Stride<0, 0> > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_finite >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_finite.hpp:29:20: required from ‘void stan::math::check_finite(const char*, const char*, const T_y&) [with T_y = Eigen::Array]’ 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 63 | check_finite(function, "Location parameter", mu_val); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_positive, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_positive.hpp:29:20: required from ‘void stan::math::check_positive(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 64 | check_positive(function, "Scale parameter", sigma_val); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, 0, Eigen::Stride<0, 0> > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_nonnegative, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_nonnegative.hpp:26:20: required from ‘void stan::math::check_nonnegative(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]’ 26 | elementwise_check([](double x) { return x >= 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 27 | "nonnegative"); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/binomial_logit_lpmf.hpp:60:20: required from ‘stan::return_type_t stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector; T_N = std::vector; T_prob = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 60 | check_nonnegative(function, "Population size parameter", N_val); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_gMAP.h:1149:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1149 | lp_accum__.add(stan::math::binomial_logit_lpmf(r, r_n, 1150 | theta)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase, 0, Eigen::Stride<0, 0> > > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 1, -1, false> >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from ‘ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; ResultType = double; Scalar = double]’ 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from ‘const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long int]’ 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]’ 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]’ 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/matrix_exp_action_handler.hpp:106:49: required from here 106 | return x.cwiseAbs().rowwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block >, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block >, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block >, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block >, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, true>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, true>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, true>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, 1, -1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, 1, -1, true>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from ‘class Eigen::internal::visitor_evaluator, const Eigen::Block, 0>, -1, 1, false> > >’ 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from ‘void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >]’ 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:325:54: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Block, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_not_nan > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:28:20: required from ‘void stan::math::check_not_nan(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 62 | check_not_nan(function, "Random variable", y_val); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp: In instantiation of ‘void stan::math::elementwise_check(const F&, const char*, const char*, const T&, const char*, const Indexings& ...) [with F = check_nonnegative > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]’: /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_nonnegative.hpp:26:20: required from ‘void stan::math::check_nonnegative(const char*, const char*, const T_y&) [with T_y = Eigen::ArrayWrapper >]’ 26 | elementwise_check([](double x) { return x >= 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 27 | "nonnegative"); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:46:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 46 | check_nonnegative(function, "Random variable", y_val); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/elementwise_check.hpp:153:24: warning: comparison of integer expressions of different signedness: ‘size_t’ {aka ‘long unsigned int’} and ‘Eigen::EigenBase > >::Index’ {aka ‘long int’} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from ‘Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 1, -1, false>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from ‘int stan::services::standalone_generate(const Model&, const Eigen::MatrixXd&, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; Eigen::MatrixXd = Eigen::Matrix]’ 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0: required from ‘SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_gMAP.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 16, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 16, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 16, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:280:48: required from ‘void Eigen::internal::outer_product_selector_run(Dst&, const Lhs&, const Rhs&, const Func&, const false_type&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Func = generic_product_impl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]’ 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from ‘void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:28:39: required from here 28 | m2_ += (q - m_) * delta.transpose(); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, true>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:333: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 306 | typedef typename Traits::LhsPacket LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of ‘class Eigen::internal::gemv_traits’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from ‘struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>’ 314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:347:132: required from ‘static void Eigen::internal::gemv_dense_selector<2, 1, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::run( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 348 | actualLhs.rows(), actualLhs.cols(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | LhsMapper(actualLhs.data(), actualLhs.outerStride()), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 350 | RhsMapper(actualRhsPtr, 1), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~ 351 | dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 352 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]’ 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:42:3: note: in definition of macro ‘PACKET_DECL_COND_PREFIX’ 42 | prefix ## name ## Packet | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from ‘Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]’ 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from ‘Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]’ 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:29:31: required from ‘T_return stan::math::internal::hypergeometric_3F2_infsum(const Ta&, const Tb&, const Tz&, double, int) [with Ta = std::vector; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:123:47: required from ‘auto stan::math::hypergeometric_3F2(const Ta&, const Tb&, const Tz&) [with Ta = std::vector; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]’ 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/hypergeometric_3F2.hpp:148:28: required from ‘auto stan::math::hypergeometric_3F2(const std::initializer_list<_Tp>&, const std::initializer_list<_Value>&, const Tz&) [with Ta = double; Tb = double; Tz = double; stan::require_all_stan_scalar_t* = 0]’ 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/inv_inc_beta.hpp:77:0: required from here 77 | + log(hypergeometric_3F2({a_val, a_val, one_m_b}, {ap1, ap1}, w)) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from ‘static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 514 | abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Block, -1, 1, false>]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:359:56: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 199 | * CubicInterp(_gk_1.dot(_pk_1), _alphak_1, _fk - _fk_1, /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); stanExports_gMAP.h:1007:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1007 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 0, 1)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Array; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Array; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Array; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::Array; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = var_value; T_scale = Eigen::Matrix, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1019:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1019 | lp_accum__.add(stan::math::normal_lpdf(xi_eta, 1020 | ((stan::model::rvalue(beta, "beta", 1021 | stan::model::index_uni(1)) - 1022 | stan::model::rvalue(beta_raw_guess, 1023 | "beta_raw_guess", stan::model::index_uni(1), 1024 | stan::model::index_uni(1))) / 1025 | stan::model::rvalue(beta_raw_guess, 1026 | "beta_raw_guess", stan::model::index_uni(2), 1027 | stan::model::index_uni(1))), 1028 | stan::math::divide(tau_group, 1029 | stan::model::rvalue(beta_raw_guess, 1030 | "beta_raw_guess", stan::model::index_uni(2), 1031 | stan::model::index_uni(1))))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1053:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1053 | lp_accum__.add(stan::math::normal_lpdf(beta, 1054 | stan::model::rvalue(beta_prior_stan, 1055 | "beta_prior_stan", stan::model::index_uni(1)), 1056 | stan::model::rvalue(beta_prior_stan, 1057 | "beta_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/uniform_lpdf.hpp:85:0: required from ‘stan::return_type_t stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_low = Eigen::Matrix; T_high = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 85 | logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta); stanExports_gMAP.h:1082:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1082 | lp_accum__.add(stan::math::uniform_lpdf(tau, 1083 | stan::model::rvalue(tau_prior_stan, 1084 | "tau_prior_stan", stan::model::index_uni(1)), 1085 | stan::model::rvalue(tau_prior_stan, 1086 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 106 | logp += sum((alpha_val - 1.0) * log_y) * N / max_size(alpha, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 96 | logp -= sum((alpha_val + 1.0) * log_y) * N / max_size(y, alpha); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:74:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 74 | = N * NEG_LOG_SQRT_TWO_PI - 0.5 * sum(square(logy_m_mu) * inv_sigma_sq); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:0: required from ‘stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix, -1, 1>; T_scale = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]’ 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); stanExports_gMAP.h:1144:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 1144 | lp_accum__.add(stan::math::normal_lpdf(y, theta, y_se)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, true>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:166:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 372 | hCoeffs.tail(n-i-1) += (conj(h)*RealScalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:0: required from ‘stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_inv_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); stanExports_gMAP.h:1091:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1091 | lp_accum__.add(stan::math::gamma_lpdf(tau, 1092 | stan::model::rvalue(tau_prior_stan, 1093 | "tau_prior_stan", stan::model::index_uni(1)), 1094 | stan::model::rvalue(tau_prior_stan, 1095 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:102:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 102 | logp -= sum(beta_val * inv_y) * N / max_size(y, beta); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:74:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 74 | = N * NEG_LOG_SQRT_TWO_PI - 0.5 * sum(square(logy_m_mu) * inv_sigma_sq); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/accumulator.hpp:53:35: required from ‘void stan::math::accumulator >::add(const S&) [with S = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_matrix_t* = 0; T = double; = void]’ 53 | buf_.push_back(stan::math::sum(m)); | ~~~~~~~~~~~~~~~^~~ stanExports_gMAP.h:1134:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1134 | lp_accum__.add(stan::math::multiply( 1135 | stan::model::rvalue(tau_raw_guess, 1136 | "tau_raw_guess", stan::model::index_uni(2)), 1137 | tau_raw)); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/poisson_log_lpmf.hpp:76:0: required from ‘stan::return_type_t stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = false; T_n = std::vector; T_log_rate = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 76 | logp -= sum(exp_alpha) * N / math::size(alpha); stanExports_gMAP.h:1155:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1155 | lp_accum__.add(stan::math::poisson_log_lpmf(count, 1156 | stan::math::add(log_offset, theta))); stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/newton.hpp:56:0: required from ‘int stan::services::optimize::newton(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, bool, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 56 | lp = model.template log_prob(cont_vector, disc_vector, 57 | &message); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:502:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 502 | = stan::services::optimize::newton(model, *init_context_ptr, 503 | random_seed, id, init_radius, 504 | num_iterations, 505 | save_iterations, 506 | interrupt, logger, 507 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from ‘static void Eigen::internal::generic_product_impl::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix; LhsT = Eigen::Matrix; RhsT = Eigen::Transpose >; Func = Eigen::internal::assign_op; Scalar = double; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); | ~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2, Eigen::Stride<0, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2, Eigen::Stride<0, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 2, Eigen::Stride<0, 0> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:40: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, true>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; Dest = Eigen::Block, -1, 1, false>; typename Dest::Scalar = double]’ 296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; Rhs = Eigen::Transpose >; Dest = Eigen::Block, 1, -1, false>; int StorageOrder = 1; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ In file included from /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:31: /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’: /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’: /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: required from ‘struct boost::concepts::requirement_ > > >)>’ 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’ 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement::failed() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/range/algorithm/equal.hpp:174:13: required from ‘bool boost::range::equal(const SinglePassRange1&, const SinglePassRange2&) [with SinglePassRange1 = boost::iterator_range<__gnu_cxx::__normal_iterator > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/iterator_range_core.hpp:644:32: required from ‘bool boost::operator==(const iterator_range&, const iterator_range&) [with Iterator1T = __gnu_cxx::__normal_iterator >; Iterator2T = __gnu_cxx::__normal_iterator >]’ 644 | return boost::equal( l, r ); | ~~~~~~~~~~~~^~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from ‘bool boost::algorithm::split_iterator::equal(const boost::algorithm::split_iterator&) const [with IteratorT = __gnu_cxx::__normal_iterator >]’ 359 | m_Match==Other.m_Match && /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:649:26: required from ‘static bool boost::iterators::iterator_core_access::equal(const Facade1&, const Facade2&, mpl_::true_) [with Facade1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; mpl_::true_ = mpl_::bool_]’ 649 | return f1.equal(f2); | ~~~~~~~~^~~~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator==(const iterator_facade&, const iterator_facade&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference1 = long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/local/lib/R/library/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: warning: ‘this’ pointer is null [-Wnonnull] 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:74: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:337: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 62 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 63 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, false>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:81:75: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 81 | gemm_pack_rhs pack_rhs; | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:125:16: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::CopyConstructible::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 167 | BOOST_CONCEPT_USAGE(CopyConstructible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::IncrementableIteratorConcept::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 136 | BOOST_CONCEPT_USAGE(IncrementableIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::EqualityComparable::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 233 | BOOST_CONCEPT_USAGE(EqualityComparable) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: required from ‘struct boost::Convertible’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 208 | BOOST_CONCEPT_USAGE(Convertible) { | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 158 | BOOST_CONCEPT_USAGE(SinglePassIteratorConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp: In instantiation of ‘boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]’: /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47: required from ‘static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]’ 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: required from ‘struct boost::SinglePassRangeConcept > > >’ 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of ‘template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]’ 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from ‘const bool boost::concepts::not_satisfied > > > >::value’ 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from ‘struct boost::concepts::not_satisfied > > > >’ 45 | typedef boost::integral_constant type; | ^~~~ /usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from ‘typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]’ 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ /usr/include/c++/14/bits/stl_vector.h:1673:21: required from ‘void std::vector<_Tp, _Alloc>::_M_range_initialize(_InputIterator, _InputIterator, std::input_iterator_tag) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]’ 1673 | for (; __first != __last; ++__first) | ~~~~~~~~^~~~~~~~~ /usr/include/c++/14/bits/stl_vector.h:711:23: required from ‘std::vector<_Tp, _Alloc>::vector(_InputIterator, _InputIterator, const allocator_type&) [with _InputIterator = boost::iterators::transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]’ 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from ‘SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]’ 186 | SequenceSequenceT Tmp(itBegin, itEnd); /usr/local/lib/R/library/BH/include/boost/algorithm/string/split.hpp:158:0: required from ‘SequenceSequenceT& boost::algorithm::split(SequenceSequenceT&, RangeT&&, PredicateT, token_compress_mode_type) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]’ 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); /usr/local/lib/R/library/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:19:0: required from here 19 | boost::split(parts, variable, boost::is_any_of(":")); /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:20:48: warning: ‘this’ pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function ‘boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]’ 37 | ~model() | ^ /usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9: note: in expansion of macro ‘BOOST_CONCEPT_USAGE’ 284 | BOOST_CONCEPT_USAGE(SinglePassRangeConcept) | ^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from /usr/local/lib/R/library/RcppEigen/include/Eigen/Core:166: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h: In instantiation of ‘Index Eigen::internal::first_default_aligned(const Scalar*, Index) [with Scalar = double; Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from ‘static void Eigen::internal::selfadjoint_matrix_vector_product::run(Index, const Scalar*, Index, const Scalar*, Scalar*, Scalar) [with Scalar = double; Index = long int; int StorageOrder = 0; int UpLo = 1; bool ConjugateLhs = false; bool ConjugateRhs = false; int Version = 0]’ 89 | Index alignedStart = (starti) + internal::first_default_aligned(&res[starti], endi-starti); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from ‘static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]’ 227 | internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 228 | int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 229 | ( | ^ 230 | lhs.rows(), // size | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | actualRhsPtr, // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | actualDestPtr, // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | actualAlpha // scale factor | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 235 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’ 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 500 | return first_aligned::alignment>(array, size); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:169:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheRight(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 169 | this->col(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:304:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 131 | this->row(0) -= tau * tmp; | ~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from ‘void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]’ 132 | bottom.noalias() -= tau * essential * tmp; | ~~~~^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:332:31: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const T&) [with T = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 850 | typename plain_matrix_type::type tmp(src); | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]’ 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from ‘Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]’ 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:225:24: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’ 225 | return Base::_set(other); | ~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:184:17: required from ‘static void Eigen::internal::general_matrix_matrix_product::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking&, Eigen::internal::GemmParallelInfo*) [with Index = long int; LhsScalar = double; int LhsStorageOrder = 0; bool ConjugateLhs = false; RhsScalar = double; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; ResScalar = double]’ 184 | pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14: required from ‘void Eigen::internal::gemm_functor::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Dest = Eigen::Matrix; BlockingType = Eigen::internal::gemm_blocking_space<0, double, double, -1, -1, -1, 1, false>]’ 230 | Gemm::run(rows, cols, m_lhs.cols(), | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ 231 | &m_lhs.coeffRef(row,0), m_lhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 232 | &m_rhs.coeffRef(0,col), m_rhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 233 | (Scalar*)&(m_dest.coeffRef(row,col)), m_dest.innerStride(), m_dest.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 234 | m_actualAlpha, m_blocking, info); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/Parallelizer.h:114:7: required from ‘void Eigen::internal::parallelize_gemm(const Functor&, Index, Index, Index, bool) [with bool Condition = true; Functor = gemm_functor, Eigen::Matrix, Eigen::Transpose >, Eigen::Matrix, gemm_blocking_space<0, double, double, -1, -1, -1, 1, false> >; Index = long int]’ 114 | func(0,rows, 0,cols); | ~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:509:9: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]’ 508 | internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 509 | (GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), a_lhs.cols(), Dest::Flags&RowMajorBit); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from ‘class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from ‘class Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >’ 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from ‘typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]’ 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 1; bool ConjugateLhs = false; int RhsStorageOrder = 0; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 346 | pack_rhs_panel(blockB+j2*actual_kc, | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ 347 | rhs.getSubMapper(actual_k2+panelOffset, actual_j2), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 348 | panelLength, actualPanelWidth, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 349 | actual_kc, panelOffset); | ~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]’ 783 | triangular_product_impl::run(dst, lhs, rhs.nestedExpression(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from ‘static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]’ 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from ‘static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]’ 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 2>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 2>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 2>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 2>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 2>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 2>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 1>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, 1>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, 1>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base >, 1>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl >, 1>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product >, 1>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 5>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, -1, -1, false>, 5>, Eigen::Matrix, 0, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, -1, -1, false>, 5>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, -1, -1, false>, 5>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:361:25: required from ‘static bool Eigen::internal::ldlt_inplace<1>::unblocked(MatrixType&, TranspositionType&, Workspace&, Eigen::internal::SignMatrix&) [with MatrixType = Eigen::Matrix; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]’ 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from ‘Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]’ 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from ‘const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]’ 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/err/check_pos_definite.hpp:45:67: required from ‘void stan::math::check_pos_definite(const char*, const char*, const EigMat&) [with EigMat = Eigen::Matrix; stan::require_matrix_t* = 0]’ 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/validate_dense_inv_metric.hpp:21:0: required from here 21 | stan::math::check_pos_definite("check_pos_definite", "inv_metric", 22 | inv_metric); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs, 4, 1, false, true>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 233 | gemm_pack_rhs pack_rhs_panel; | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:42: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true>, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:57: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:73:50: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]’ 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, Eigen::DenseShape, Eigen::DenseShape, 7>’ 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from ‘static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::sub_assign_op&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Transpose, -1, -1, false>, 1, -1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>]’ 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: required from ‘ExpressionType& Eigen::NoAlias::operator-=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>; ExpressionType = Eigen::Block, -1, -1, false>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’ 59 | call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from ‘static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’ 319 | pack_lhs_panel(blockA, lhs.getSubMapper(i2,absolute_j2), | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 320 | actualPanelWidth, actual_mc, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 321 | actual_kc, j2); | ~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]’ 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from ‘void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]’ 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from ‘static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long int]’ 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from ‘static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]’ 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2100:82: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2100 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2102:56: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2102 | HalfPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] 2103 | QuarterPacketSize = unpacket_traits::size, | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2103:62: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from ‘struct Eigen::internal::traits >’ 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from ‘class Eigen::Matrix’ 178 | class Matrix | ^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 150 | Matrix triangularBuffer(a); | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of ‘struct Eigen::internal::find_best_packet’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from ‘class Eigen::DenseBase, 0> >’ 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from ‘static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long int; int Mode = 1; int LhsStorageOrder = 0; bool ConjugateLhs = false; int RhsStorageOrder = 1; bool ConjugateRhs = false; int ResInnerStride = 1; int Version = 0]’ 153 | triangularBuffer.diagonal().setZero(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’ 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, Dest::InnerStrideAtCompileTime> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 443 | ::run( | ~~~~~^ 444 | stripedRows, stripedCols, stripedDepth, // sizes | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 445 | &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 446 | &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 447 | &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 448 | actualAlpha, blocking | ~~~~~~~~~~~~~~~~~~~~~ 449 | ); | ~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument ‘Eigen::internal::unpacket_traits<__vector(2) double>::half’ {aka ‘__m128d’} [-Wignored-attributes] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, false>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from ‘static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]’ 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from ‘ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]’ 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:444:18: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:303:32: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from ‘void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, Eigen::Transpose >, 1> >; Functor = Eigen::internal::assign_op; int Version = 1; Eigen::Index = long int]’ 654 | m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col)); | ~~~~~~~~~~~^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from ‘Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Derived = Eigen::Block, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]’ 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from ‘Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:31:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:142:7: required from ‘Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::coeff(Eigen::Index) const [with Derived = Eigen::Block, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long int]’ 142 | EIGEN_STATIC_ASSERT(internal::evaluator::Flags & LinearAccessBit, | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:182:19: required from ‘Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::operator()(Eigen::Index) const [with Derived = Eigen::Block, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long int]’ 182 | return coeff(index); | ~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:53: required from ‘void Eigen::internal::make_block_householder_triangular_factor(TriangularFactorType&, const VectorsType&, const CoeffsType&) [with TriangularFactorType = Eigen::Matrix; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: required from ‘void Eigen::internal::apply_block_householder_on_the_left(MatrixType&, const VectorsType&, const CoeffsType&, bool) [with MatrixType = Eigen::Block, -1, -1, false>; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]’ 92 | if(forward) make_block_householder_triangular_factor(T, vectors, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:399:46: required from ‘void Eigen::HouseholderSequence::applyThisOnTheLeft(Dest&, Workspace&, bool) const [with Dest = Eigen::Matrix; Workspace = Eigen::Matrix; VectorsType = Eigen::Matrix; CoeffsType = Eigen::Matrix; int Side = 1]’ 399 | apply_block_householder_on_the_left(sub_dst, sub_vecs, m_coeffs.segment(k, bs), !m_reverse); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:320:29: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from ‘Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, false>; Scalar = double]’ 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from ‘class Eigen::Map, 0, Eigen::OuterStride<> >’ 94 | template class Map | ^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:39:18: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:57: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:43: required from ‘static void Eigen::internal::gemv_dense_selector<2, 0, false>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; typename Dest::Scalar = double]’ 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:42: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, 1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:301:29: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, false> >, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, false> >, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 123 | Base::operator=(a); /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from ‘stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]’ 68 | *this = other; /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from ‘stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]’ 722 | : val_(x), /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from ‘stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]’ 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply_lower_tri_self_transpose.hpp:27:0: required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value >; stan::require_rev_matrix_t* = 0]’ 27 | arena_t res = arena_L_val.template triangularView() /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cov_matrix_constrain.hpp:59:0: required from here 59 | return multiply_lower_tri_self_transpose(L); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 38 | arena_t res = arena_A_val * arena_B_val; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from ‘Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]’ 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 1; int _MaxRows = -1; int _MaxCols = -1]’ 423 | : Base(other.derived()) | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from ‘stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]’ 18 | return std::forward(a); | ^ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from ‘Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]’ 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from ‘auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]’ 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/wishart_rng.hpp:34:0: required from here 34 | return crossprod(B * llt_of_S.matrixU()); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, 1, false> >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, 1, false> >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block, -1, -1, false>; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from ‘static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long int; int Mode = 2; bool Conjugate = false]’ 78 | rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from ‘static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; int Side = 1; int Mode = 2]’ 71 | triangular_solve_vector | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, true>, 1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, -1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:32: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]’ 194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from ‘Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, 1, false>]’ 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, true>, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, const Eigen::Block, -1, 1, true>, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from ‘struct Eigen::internal::plain_object_eval, -1, 1, true>, Eigen::Dense>’ 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from ‘struct Eigen::internal::generic_product_impl, const Eigen::Block, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’ 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from ‘static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; Scalar = double]’ 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix]’ 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Matrix, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, Eigen::Matrix, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, Eigen::Matrix, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Matrix, 0, 7>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, 1, -1, false>, Eigen::Matrix, 0>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/services/util/run_adaptive_sampler.hpp:57:0: required from ‘void stan::services::util::run_adaptive_sampler(Sampler&, Model&, std::vector&, int, int, int, int, bool, RNG&, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, size_t, size_t) [with Sampler = stan::mcmc::adapt_dense_e_nuts, boost::random::linear_congruential_engine > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; size_t = long unsigned int]’ 57 | sampler.init_stepsize(logger); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:97:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 97 | util::run_adaptive_sampler( 98 | sampler, model, cont_vector, num_warmup, num_samples, num_thin, refresh, 99 | save_warmup, rng, interrupt, logger, sample_writer, diagnostic_writer); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp:150:0: required from ‘int stan::services::sample::hmc_nuts_dense_e_adapt(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, int, int, int, bool, int, double, double, int, double, double, double, double, unsigned int, unsigned int, unsigned int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP]’ 150 | return hmc_nuts_dense_e_adapt( 151 | model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup, 152 | num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter, 153 | max_depth, delta, gamma, kappa, t0, init_buffer, term_buffer, window, 154 | interrupt, logger, init_writer, sample_writer, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:638:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 637 | return_code = stan::services::sample 638 | ::hmc_nuts_dense_e_adapt(model, *init_context_ptr, 639 | random_seed, id, init_radius, 640 | num_warmup, num_samples, 641 | num_thin, save_warmup, refresh, 642 | stepsize, stepsize_jitter, max_depth, 643 | delta, gamma, kappa, 644 | t0, init_buffer, term_buffer, window, 645 | interrupt, logger, init_writer, 646 | *sample_writer_ptr, diagnostic_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = add_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix, -1, 1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]’ 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_gMAP.h:997:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]’ 997 | stan::math::add(stan::math::multiply(X_param, beta), stanExports_gMAP.h:1644:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]’ 1644 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from ‘double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream]’ 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1183:0: required from ‘SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_gMAP.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/access_helpers.hpp:92:0: required from ‘void stan::model::internal::assign_impl(T1&&, T2&&, const char*) [with T1 = Eigen::Matrix&; T2 = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >; stan::require_all_eigen_t* = 0]’ 92 | x = std::forward(y); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from ‘void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]’ 60 | internal::assign_impl(x, std::forward(y), name); stanExports_gMAP.h:1286:0: required from ‘void model_gMAP_namespace::model_gMAP::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’ 1286 | stan::model::assign(theta, 1287 | stan::math::add(stan::math::multiply(X_param, beta), 1288 | stan::model::rvalue(eta, "eta", 1289 | stan::model::index_multi(group_index))), 1290 | "assigning variable theta"); stanExports_gMAP.h:1633:0: required from ‘void model_gMAP_namespace::model_gMAP::write_array(RNG&, std::vector&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 1633 | write_array_impl(base_rng, params_r, params_i, vars, 1634 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1105:0: required from ‘SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_gMAP.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 341 | dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:74: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false> >, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false> >, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix, 1>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix, 1> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix, 1> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from ‘class Eigen::internal::dense_product_base, Eigen::Matrix, 1, 8>’ 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from ‘class Eigen::ProductImpl, Eigen::Matrix, 1, Eigen::Dense>’ 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from ‘class Eigen::Product, Eigen::Matrix, 1>’ 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 1, -1, false>, 1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 1, -1, false>, 1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::InnerStride<> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::InnerStride<> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::InnerStride<> >, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:106: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from ‘class Eigen::PlainObjectBase >’ 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 0>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, 0>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 0> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 0> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from ‘class Eigen::Diagonal, 0>’ 63 | template class Diagonal | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, 1, -1, false>, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, 1, -1, false>, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, 1, -1, false>, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from ‘class Eigen::CwiseNullaryOp, Eigen::Matrix >’ 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from ‘Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]’ 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from ‘Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]’ 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:151:29: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block, -1, -1, false>, -1, -1, true>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:32: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase, -1, -1, false>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, -1, false> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, -1, -1, false> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase, -1, -1, false>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense, -1, -1, false, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase >, -1, -1, true>, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, -1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from ‘class Eigen::internal::BlockImpl_dense >, -1, -1, true, true>’ 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from ‘static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; typename Dest::Scalar = double]’ 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from ‘class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >’ 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from ‘static void Eigen::internal::triangular_matrix_vector_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, const ResScalar&) [with Index = long int; int Mode = 6; LhsScalar = double; bool ConjLhs = false; RhsScalar = double; bool ConjRhs = false; int Version = 0; ResScalar = double]’ 137 | res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from ‘static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’ 327 | internal::triangular_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 328 | | ~~~~~~~~~ 332 | ::run(actualLhs.rows(),actualLhs.cols(), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 333 | actualLhs.data(),actualLhs.outerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 334 | actualRhsPtr,1, | ~~~~~~~~~~~~~~~ 335 | dest.data(),dest.innerStride(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 336 | actualAlpha); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:780:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]’ 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:27: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op]’ 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: required from ‘void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if<(! evaluator_assume_aliasing::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]’ 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from ‘Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]’ 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:31: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from ‘const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long int]’ 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from ‘Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]’ 40 | _Hk = Hupd * _Hk * Hupd.transpose(); /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from ‘int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]’ 246 | Scalar B0fact = _qn.update(yk, sk, true); /usr/local/lib/R/library/StanHeaders/include/src/stan/services/optimize/bfgs.hpp:117:0: required from ‘int stan::services::optimize::bfgs(Model&, const stan::io::var_context&, unsigned int, unsigned int, double, double, double, double, double, double, double, int, bool, int, stan::callbacks::interrupt&, stan::callbacks::logger&, stan::callbacks::writer&, stan::callbacks::writer&) [with Model = model_gMAP_namespace::model_gMAP; bool jacobian = false]’ 117 | ret = bfgs.step(); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:517:0: required from ‘int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Rcpp::List = Rcpp::Vector<19>]’ 517 | = stan::services::optimize::bfgs(model, *init_context_ptr, 518 | random_seed, id, init_radius, 519 | init_alpha, 520 | tol_obj, 521 | tol_rel_obj, 522 | tol_grad, 523 | tol_rel_grad, 524 | tol_param, 525 | num_iterations, 526 | save_iterations, 527 | refresh, 528 | interrupt, logger, 529 | init_writer, sample_writer); /usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1215:0: required from ‘SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]’ 1215 | ret = command(args, model_, holder, names_oi_tidx_, 1216 | fnames_oi_, base_rng); stanExports_gMAP.cc:15:0: required from here 15 | .method("call_sampler", &rstan::stan_fit ::call_sampler) /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, -1, -1, false> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, -1, -1, false> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator >, -1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator >, -1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >’ 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: required from ‘void Eigen::internal::call_dense_assignment_loop(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = sub_assign_op]’ 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from ‘static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]’ 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:238:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>& Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::operator=(const Eigen::EigenBase&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 1>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’ 238 | return Base::operator=(other); | ~~~~~~~~~~~~~~~^~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from ‘static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]’ 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:434:55: required from ‘void Eigen::internal::tridiagonalization_inplace(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with MatrixType = Eigen::Matrix; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]’ 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from ‘Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from ‘Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]’ 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from ‘class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’ 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from ‘class Eigen::CwiseUnaryView, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >’ 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from ‘void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::sum > >(const std::vector, arena_allocator > >&)::]’ 21 | inline void chain() final { rev_functor_(*this); } /usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ stanExports_gMAP.h: In instantiation of ‘void model_gMAP_namespace::model_gMAP::write_array_impl(RNG&, VecR&, VecI&, VecVar&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; VecR = Eigen::Matrix; VecI = std::vector; VecVar = Eigen::Matrix; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]’: stanExports_gMAP.h:1616:0: required from ‘void model_gMAP_namespace::model_gMAP::write_array(RNG&, Eigen::Matrix&, Eigen::Matrix&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]’ 1616 | write_array_impl(base_rng, params_r, params_i, vars, 1617 | emit_transformed_parameters, emit_generated_quantities, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:140:0: required from ‘void stan::model::model_base_crtp::write_array(boost::random::ecuyer1988&, Eigen::VectorXd&, Eigen::VectorXd&, bool, bool, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; boost::random::ecuyer1988 = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ 140 | return static_cast(this)->template write_array( 141 | rng, theta, vars, include_tparams, include_gqs, msgs); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:136:0: required from here 136 | void write_array(boost::ecuyer1988& rng, Eigen::VectorXd& theta, stanExports_gMAP.h:1191: warning: unused variable ‘jacobian__’ [-Wunused-variable] 1191 | constexpr bool jacobian__ = false; /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp >, void>::apply(const Eigen::ArrayWrapper >&)::, const Eigen::ArrayWrapper > > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:92:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 92 | partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y; stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix; VecI = Eigen::Matrix; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1639:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(Eigen::Matrix&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1639 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:115:0: required from ‘double stan::model::model_base_crtp::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ 115 | return static_cast(this)->template log_prob(theta, 116 | msgs); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:113:0: required from here 113 | inline double log_prob_propto(Eigen::VectorXd& theta, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | logp -= sum((alpha_val + 1.0) * log_y) * N / max_size(y, alpha); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix; VecI = Eigen::Matrix; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1639:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(Eigen::Matrix&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1639 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:115:0: required from ‘double stan::model::model_base_crtp::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ 115 | return static_cast(this)->template log_prob(theta, 116 | msgs); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:113:0: required from here 113 | inline double log_prob_propto(Eigen::VectorXd& theta, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from ‘class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > > >’ 39 | template class ArrayBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper >, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper > >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/lognormal_lpdf.hpp:70:0: required from ‘stan::return_type_t stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 70 | const auto& logy_m_mu = to_ref(log_y - mu_val); stanExports_gMAP.h:1109:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix; VecI = Eigen::Matrix; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1109 | lp_accum__.add(stan::math::lognormal_lpdf(tau, 1110 | stan::model::rvalue(tau_prior_stan, 1111 | "tau_prior_stan", stan::model::index_uni(1)), 1112 | stan::model::rvalue(tau_prior_stan, 1113 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1639:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(Eigen::Matrix&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1639 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:115:0: required from ‘double stan::model::model_base_crtp::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ 115 | return static_cast(this)->template log_prob(theta, 116 | msgs); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:113:0: required from here 113 | inline double log_prob_propto(Eigen::VectorXd& theta, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]’ 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from ‘double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:20:0: required from here 20 | double T(diag_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from ‘stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]’ 47 | return m.sum(); | ~~~~~^~ /usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/inv_gamma_lpdf.hpp:96:0: required from ‘stan::return_type_t stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix; T_shape = Eigen::Matrix; T_scale = Eigen::Matrix; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]’ 96 | logp -= sum((alpha_val + 1.0) * log_y) * N / max_size(y, alpha); stanExports_gMAP.h:1100:0: required from ‘stan::scalar_type_t model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix; VecI = Eigen::Matrix; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]’ 1100 | lp_accum__.add(stan::math::inv_gamma_lpdf(tau, 1101 | stan::model::rvalue(tau_prior_stan, 1102 | "tau_prior_stan", stan::model::index_uni(1)), 1103 | stan::model::rvalue(tau_prior_stan, 1104 | "tau_prior_stan", stan::model::index_uni(2)))); stanExports_gMAP.h:1639:0: required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(Eigen::Matrix&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]’ 1639 | return log_prob_impl(params_r, params_i, pstream); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:115:0: required from ‘double stan::model::model_base_crtp::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix; std::ostream = std::basic_ostream]’ 115 | return static_cast(this)->template log_prob(theta, 116 | msgs); /usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:113:0: required from here 113 | inline double log_prob_propto(Eigen::VectorXd& theta, /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from ‘class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>’ 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from ‘class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>’ 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from ‘class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>’ 103 | template class Block | ^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: required from ‘static void Eigen::internal::gemv_dense_selector<1, StorageOrder, BlasCompatible>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]’ 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from ‘class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>’ 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from ‘class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >’ 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase > >, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from ‘class Eigen::DenseCoeffsBase > >, 2>’ 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase > > >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase > > >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from ‘class Eigen::TransposeImpl >, Eigen::Dense>’ 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from ‘class Eigen::Transpose > >’ 52 | template class Transpose | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 1>’ 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from ‘class Eigen::DenseCoeffsBase >, -1, 1, true>, 3>’ 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from ‘class Eigen::DenseBase >, -1, 1, true> >’ 41 | template class DenseBase | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from ‘class Eigen::MatrixBase >, -1, 1, true> >’ 48 | template class MatrixBase | ^~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from ‘class Eigen::MapBase >, -1, 1, true>, 0>’ 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from ‘struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’ 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from ‘struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >’ 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from ‘struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’ 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long int]’: /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from ‘static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]’ 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from ‘typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]’ 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from ‘static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]’ 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from ‘typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]’ 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from ‘static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]’ 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from ‘Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from ‘Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]’ 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from ‘Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]’ 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from ‘double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]’ 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; /usr/local/lib/R/library/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:21:0: required from here 21 | double T(dense_e_point& z) { /usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits::type’ {aka ‘__m128d’} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ g++ -std=gnu++17 -shared -L/usr/lib64/R/lib -Wl,-z,relro -Wl,--as-needed -Wl,-z,pack-relative-relocs -Wl,-z,now -specs=/usr/lib/rpm/redhat/redhat-hardened-ld-errors -specs=/usr/lib/rpm/redhat/redhat-hardened-ld -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1 -Wl,--build-id=sha1 -o RBesT.so RcppExports.o stanExports_gMAP.o -L/usr/lib64 -Wl,-rpath,/usr/lib64 -ltbb -ltbbmalloc -L/usr/local/lib/R/library/RcppParallel/lib/ -Wl,-rpath,/usr/local/lib/R/library/RcppParallel/lib/ -ltbb -ltbbmalloc -L/usr/lib64/R/lib -lR installing to /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64/usr/local/lib/R/library/00LOCK-RBesT/00new/RBesT/libs ** R ** data *** moving datasets to lazyload DB ** demo ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices converting help for package ‘RBesT’ finding HTML links ... done AS html BinaryExactCI html Curry html RBesT-package html SimSum html automixfit html chains2sample html colVars html colitis html crohn html dBetaBinomial html decision1S html decision1S_boundary html decision2S html decision2S_boundary html dlink-set html ess html fill html forest_plot html gMAP html integrate_density_log html knn html likelihood html lodds html logLik.EM html log_inv_logit html mix html mixbeta html mixcombine html mixdiff html mixdist3 html mixfit html mixgamma html mixlink html mixmvnorm html mixnorm html mixplot html mixstanvar html oc1S html oc2S html plot.EM html plot.gMAP html finding level-2 HTML links ... done pos1S html pos2S html postmix html preddist html predict.gMAP html robustify html support html transplant html uniroot_int html ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** checking absolute paths in shared objects and dynamic libraries ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (RBesT) + test -d RBesT/src + cd RBesT/src + rm -f RcppExports.o stanExports_gMAP.o RBesT.so + rm -f /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64/usr/local/lib/R/library/R.css + find /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64/usr/local/lib/R/library -type f -exec sed -i s@/builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64@@g '{}' ';' + /usr/bin/find-debuginfo -j4 --strict-build-id -m -i --build-id-seed 1.7.3-1.fc41.copr7480677 --unique-debug-suffix -1.7.3-1.fc41.copr7480677.x86_64 --unique-debug-src-base R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 --run-dwz --dwz-low-mem-die-limit 10000000 --dwz-max-die-limit 110000000 -S debugsourcefiles.list /builddir/build/BUILD/RBesT find-debuginfo: starting Extracting debug info from 1 files DWARF-compressing 1 files sepdebugcrcfix: Updated 1 CRC32s, 0 CRC32s did match. Creating .debug symlinks for symlinks to ELF files Copying sources found by 'debugedit -l' to /usr/src/debug/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 159 blocks find-debuginfo: done + /usr/lib/rpm/check-buildroot + /usr/lib/rpm/redhat/brp-ldconfig + /usr/lib/rpm/brp-compress + /usr/lib/rpm/redhat/brp-strip-lto /usr/bin/strip + /usr/lib/rpm/brp-strip-static-archive /usr/bin/strip + /usr/lib/rpm/redhat/brp-mangle-shebangs mangling shebang in /usr/local/lib/R/library/RBesT/sbc/make_reference_rankhist.R from /usr/bin/env Rscript to #!/usr/bin/Rscript + /usr/lib/rpm/brp-remove-la-files + env /usr/lib/rpm/redhat/brp-python-bytecompile '' 1 0 -j4 + /usr/lib/rpm/redhat/brp-python-hardlink + /usr/bin/add-determinism --brp -j4 /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 Cannot initialize handler pyc: ModuleNotFoundError: No module named 'marshalparser' [src/multiprocess.rs:66:9] &cmd = Command { program: "/usr/bin/add-determinism", args: [ "/usr/bin/add-determinism", "--socket", "3", "--brp", "--handler", "ar,jar,javadoc", ], create_pidfd: false, } Bye! Bye! Bye! Bye! Processing files: R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 Provides: R-CRAN-RBesT = 1.7.3-1.fc41.copr7480677 R-CRAN-RBesT(x86-64) = 1.7.3-1.fc41.copr7480677 Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Requires: /usr/bin/Rscript libR.so()(64bit) libc.so.6()(64bit) libc.so.6(GLIBC_2.11)(64bit) libc.so.6(GLIBC_2.14)(64bit) libc.so.6(GLIBC_2.2.5)(64bit) libc.so.6(GLIBC_2.3.4)(64bit) libc.so.6(GLIBC_2.38)(64bit) libc.so.6(GLIBC_2.4)(64bit) libc.so.6(GLIBC_ABI_DT_RELR)(64bit) libgcc_s.so.1()(64bit) libgcc_s.so.1(GCC_3.0)(64bit) libgcc_s.so.1(GCC_3.3.1)(64bit) libm.so.6()(64bit) libm.so.6(GLIBC_2.2.5)(64bit) libm.so.6(GLIBC_2.29)(64bit) libstdc++.so.6()(64bit) libstdc++.so.6(CXXABI_1.3)(64bit) libstdc++.so.6(CXXABI_1.3.15)(64bit) libstdc++.so.6(CXXABI_1.3.5)(64bit) libstdc++.so.6(CXXABI_1.3.9)(64bit) libstdc++.so.6(GLIBCXX_3.4)(64bit) libstdc++.so.6(GLIBCXX_3.4.11)(64bit) libstdc++.so.6(GLIBCXX_3.4.15)(64bit) libstdc++.so.6(GLIBCXX_3.4.18)(64bit) libstdc++.so.6(GLIBCXX_3.4.19)(64bit) libstdc++.so.6(GLIBCXX_3.4.20)(64bit) libstdc++.so.6(GLIBCXX_3.4.21)(64bit) libstdc++.so.6(GLIBCXX_3.4.26)(64bit) libstdc++.so.6(GLIBCXX_3.4.29)(64bit) libstdc++.so.6(GLIBCXX_3.4.30)(64bit) libstdc++.so.6(GLIBCXX_3.4.32)(64bit) libstdc++.so.6(GLIBCXX_3.4.9)(64bit) libtbb.so.12()(64bit) rtld(GNU_HASH) Recommends: pandoc Processing files: R-CRAN-RBesT-debugsource-1.7.3-1.fc41.copr7480677.x86_64 Provides: R-CRAN-RBesT-debugsource = 1.7.3-1.fc41.copr7480677 R-CRAN-RBesT-debugsource(x86-64) = 1.7.3-1.fc41.copr7480677 Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Processing files: R-CRAN-RBesT-debuginfo-1.7.3-1.fc41.copr7480677.x86_64 Provides: R-CRAN-RBesT-debuginfo = 1.7.3-1.fc41.copr7480677 R-CRAN-RBesT-debuginfo(x86-64) = 1.7.3-1.fc41.copr7480677 debuginfo(build-id) = 356af5d3e2344f16652cae602d7c82e0c89a223b Requires(rpmlib): rpmlib(CompressedFileNames) <= 3.0.4-1 rpmlib(FileDigests) <= 4.6.0-1 rpmlib(PayloadFilesHavePrefix) <= 4.0-1 Recommends: R-CRAN-RBesT-debugsource(x86-64) = 1.7.3-1.fc41.copr7480677 Checking for unpackaged file(s): /usr/lib/rpm/check-files /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 Wrote: /builddir/build/RPMS/R-CRAN-RBesT-debugsource-1.7.3-1.fc41.copr7480677.x86_64.rpm Wrote: /builddir/build/RPMS/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64.rpm Wrote: /builddir/build/RPMS/R-CRAN-RBesT-debuginfo-1.7.3-1.fc41.copr7480677.x86_64.rpm Executing(%clean): /bin/sh -e /var/tmp/rpm-tmp.PLh5TU + umask 022 + cd /builddir/build/BUILD + cd RBesT + /usr/bin/rm -rf /builddir/build/BUILDROOT/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.x86_64 + RPM_EC=0 ++ jobs -p + exit 0 Executing(rmbuild): /bin/sh -e /var/tmp/rpm-tmp.hpI8Uz + umask 022 + cd /builddir/build/BUILD + rm -rf /builddir/build/BUILD/RBesT-SPECPARTS + rm -rf RBesT RBesT.gemspec + RPM_EC=0 ++ jobs -p + exit 0 RPM build warnings: source_date_epoch_from_changelog set but %changelog is missing Finish: rpmbuild R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm Finish: build phase for R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm INFO: chroot_scan: 1 files copied to /var/lib/copr-rpmbuild/results/chroot_scan INFO: /var/lib/mock/fedora-rawhide-x86_64-1716467991.378440/root/var/log/dnf5.log INFO: Done(/var/lib/copr-rpmbuild/results/R-CRAN-RBesT-1.7.3-1.fc41.copr7480677.src.rpm) Config(child) 2 minutes 57 seconds INFO: Results and/or logs in: /var/lib/copr-rpmbuild/results INFO: Cleaning up build root ('cleanup_on_success=True') Start: clean chroot INFO: unmounting tmpfs. Finish: clean chroot Finish: run Running RPMResults tool Package info: { "packages": [ { "name": "R-CRAN-RBesT-debugsource", "epoch": null, "version": "1.7.3", "release": "1.fc41.copr7480677", "arch": "x86_64" }, { "name": "R-CRAN-RBesT", "epoch": null, "version": "1.7.3", "release": "1.fc41.copr7480677", "arch": "src" }, { "name": "R-CRAN-RBesT", "epoch": null, "version": "1.7.3", "release": "1.fc41.copr7480677", "arch": "x86_64" }, { "name": "R-CRAN-RBesT-debuginfo", "epoch": null, "version": "1.7.3", "release": "1.fc41.copr7480677", "arch": "x86_64" } ] } RPMResults finished