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 <new-branch-name>

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
[ 27/155] libacl-0:2.3.2-1.fc40.x86_64  100% |   4.8 MiB/s |  24.4 KiB |  00m00s
[ 28/155] gawk-0:5.3.0-3.fc40.x86_64    100% |  33.5 MiB/s |   1.1 MiB |  00m00s
[ 29/155] libattr-0:2.5.2-3.fc40.x86_64 100% |   5.9 MiB/s |  18.0 KiB |  00m00s
[ 30/155] libcap-0:2.70-1.fc41.x86_64   100% |  28.1 MiB/s |  86.2 KiB |  00m00s
[ 31/155] libselinux-0:3.6-4.fc40.x86_6 100% |  85.5 MiB/s |  87.5 KiB |  00m00s
[ 32/155] fedora-repos-0:41-0.2.noarch  100% |   2.3 MiB/s |   9.3 KiB |  00m00s
[ 33/155] glibc-common-0:2.39.9000-18.f 100% |  97.4 MiB/s | 399.0 KiB |  00m00s
[ 34/155] pcre2-0:10.43-2.fc41.1.x86_64 100% |  47.3 MiB/s | 242.1 KiB |  00m00s
[ 35/155] openssl-libs-1:3.2.1-6.fc41.x 100% | 144.0 MiB/s |   2.3 MiB |  00m00s
[ 36/155] ed-0:1.20.2-1.fc41.x86_64     100% |   8.0 MiB/s |  81.9 KiB |  00m00s
[ 37/155] ansible-srpm-macros-0:1-15.fc 100% |   2.9 MiB/s |  20.9 KiB |  00m00s
[ 38/155] efi-srpm-macros-0:5-11.fc40.n 100% |  10.9 MiB/s |  22.3 KiB |  00m00s
[ 39/155] build-reproducibility-srpm-ma 100% |   2.9 MiB/s |   9.0 KiB |  00m00s
[ 40/155] dwz-0:0.15-6.fc40.x86_64      100% |  33.6 MiB/s | 137.8 KiB |  00m00s
[ 41/155] forge-srpm-macros-0:0.3.1-1.f 100% |  18.9 MiB/s |  19.4 KiB |  00m00s
[ 42/155] fonts-srpm-macros-1:2.0.5-14. 100% |  12.9 MiB/s |  26.5 KiB |  00m00s
[ 43/155] file-0:5.45-5.fc41.x86_64     100% |  16.0 MiB/s |  49.1 KiB |  00m00s
[ 44/155] fpc-srpm-macros-0:1.3-12.fc40 100% |   7.6 MiB/s |   7.8 KiB |  00m00s
[ 45/155] gnat-srpm-macros-0:6-5.fc40.n 100% |   4.3 MiB/s |   8.8 KiB |  00m00s
[ 46/155] ghc-srpm-macros-0:1.9.1-1.fc4 100% |   2.9 MiB/s |   9.0 KiB |  00m00s
[ 47/155] go-srpm-macros-0:3.6.0-1.fc41 100% |   9.1 MiB/s |  27.9 KiB |  00m00s
[ 48/155] lua-srpm-macros-0:1-13.fc40.n 100% |   4.3 MiB/s |   8.7 KiB |  00m00s
[ 49/155] kernel-srpm-macros-0:1.0-23.f 100% |   3.2 MiB/s |   9.8 KiB |  00m00s
[ 50/155] ocaml-srpm-macros-0:9-3.fc40. 100% |   4.4 MiB/s |   9.1 KiB |  00m00s
[ 51/155] package-notes-srpm-macros-0:0 100% |   9.7 MiB/s |   9.9 KiB |  00m00s
[ 52/155] openblas-srpm-macros-0:2-17.f 100% |   3.7 MiB/s |   7.7 KiB |  00m00s
[ 53/155] pyproject-srpm-macros-0:1.12. 100% |   4.4 MiB/s |  13.6 KiB |  00m00s
[ 54/155] perl-srpm-macros-0:1-53.fc40. 100% |   2.7 MiB/s |   8.4 KiB |  00m00s
[ 55/155] python-srpm-macros-0:3.12-9.f 100% |   7.8 MiB/s |  24.0 KiB |  00m00s
[ 56/155] qt6-srpm-macros-0:6.7.0-1.fc4 100% |   8.8 MiB/s |   9.0 KiB |  00m00s
[ 57/155] qt5-srpm-macros-0:5.15.13-1.f 100% |   2.8 MiB/s |   8.5 KiB |  00m00s
[ 58/155] rpm-0:4.19.1.1-2.fc41.x86_64  100% |  87.5 MiB/s | 537.6 KiB |  00m00s
[ 59/155] rust-srpm-macros-0:26.3-1.fc4 100% |   3.1 MiB/s |  12.5 KiB |  00m00s
[ 60/155] zig-srpm-macros-0:1-2.fc40.no 100% |   2.6 MiB/s |   8.0 KiB |  00m00s
[ 61/155] zip-0:3.0-40.fc40.x86_64      100% |  86.2 MiB/s | 264.8 KiB |  00m00s
[ 62/155] elfutils-0:0.191-7.fc41.x86_6 100% | 129.4 MiB/s | 530.0 KiB |  00m00s
[ 63/155] debugedit-0:5.0-16.fc41.x86_6 100% |  19.5 MiB/s |  79.7 KiB |  00m00s
[ 64/155] popt-0:1.19-6.fc40.x86_64     100% |  21.7 MiB/s |  66.7 KiB |  00m00s
[ 65/155] elfutils-libelf-0:0.191-7.fc4 100% |  50.9 MiB/s | 208.5 KiB |  00m00s
[ 66/155] readline-0:8.2-8.fc40.x86_64  100% |  52.1 MiB/s | 213.3 KiB |  00m00s
[ 67/155] rpm-build-libs-0:4.19.1.1-2.f 100% |  45.9 MiB/s |  94.0 KiB |  00m00s
[ 68/155] rpm-libs-0:4.19.1.1-2.fc41.x8 100% | 100.1 MiB/s | 307.4 KiB |  00m00s
[ 69/155] audit-libs-0:4.0.1-2.fc41.x86 100% |  40.8 MiB/s | 125.3 KiB |  00m00s
[ 70/155] zstd-0:1.5.6-1.fc41.x86_64    100% |  93.6 MiB/s | 479.3 KiB |  00m00s
[ 71/155] libeconf-0:0.6.2-1.fc41.x86_6 100% |   7.8 MiB/s |  31.9 KiB |  00m00s
[ 72/155] libsemanage-0:3.6-3.fc40.x86_ 100% |  28.4 MiB/s | 116.4 KiB |  00m00s
[ 73/155] libxcrypt-0:4.4.36-5.fc40.x86 100% |  38.4 MiB/s | 118.1 KiB |  00m00s
[ 74/155] pam-libs-0:1.6.1-1.fc41.x86_6 100% |  18.5 MiB/s |  56.9 KiB |  00m00s
[ 75/155] setup-0:2.14.5-2.fc40.noarch  100% |  75.6 MiB/s | 154.7 KiB |  00m00s
[ 76/155] xz-libs-1:5.4.6-3.fc41.x86_64 100% |  35.9 MiB/s | 110.2 KiB |  00m00s
[ 77/155] mpfr-0:4.2.1-4.fc41.x86_64    100% | 112.4 MiB/s | 345.2 KiB |  00m00s
[ 78/155] libcap-ng-0:0.8.5-1.fc41.x86_ 100% |  15.8 MiB/s |  32.3 KiB |  00m00s
[ 79/155] libblkid-0:2.40.1-1.fc41.x86_ 100% |  40.5 MiB/s | 124.3 KiB |  00m00s
[ 80/155] libsmartcols-0:2.40.1-1.fc41. 100% |  40.7 MiB/s |  83.3 KiB |  00m00s
[ 81/155] libmount-0:2.40.1-1.fc41.x86_ 100% |  50.4 MiB/s | 154.7 KiB |  00m00s
[ 82/155] libfdisk-0:2.40.1-1.fc41.x86_ 100% |  25.9 MiB/s | 159.2 KiB |  00m00s
[ 83/155] libutempter-0:1.2.1-13.fc40.x 100% |   6.4 MiB/s |  26.4 KiB |  00m00s
[ 84/155] libuuid-0:2.40.1-1.fc41.x86_6 100% |   6.9 MiB/s |  28.5 KiB |  00m00s
[ 85/155] zlib-ng-compat-0:2.1.6-3.fc41 100% |  75.2 MiB/s |  77.0 KiB |  00m00s
[ 86/155] systemd-libs-0:256~rc2-1.fc41 100% | 142.3 MiB/s | 728.4 KiB |  00m00s
[ 87/155] util-linux-core-0:2.40.1-1.fc 100% |  74.8 MiB/s | 536.2 KiB |  00m00s
[ 88/155] basesystem-0:11-20.fc40.noarc 100% |   2.3 MiB/s |   7.2 KiB |  00m00s
[ 89/155] glibc-gconv-extra-0:2.39.9000 100% | 152.3 MiB/s |   1.7 MiB |  00m00s
[ 90/155] libgcc-0:14.1.1-1.fc41.x86_64 100% |  20.8 MiB/s | 127.6 KiB |  00m00s
[ 91/155] ncurses-base-0:6.4-12.2024012 100% |  17.4 MiB/s |  88.9 KiB |  00m00s
[ 92/155] crypto-policies-0:20240521-1. 100% |  43.9 MiB/s |  90.0 KiB |  00m00s
[ 93/155] libsepol-0:3.6-3.fc40.x86_64  100% | 110.7 MiB/s | 340.1 KiB |  00m00s
[ 94/155] ca-certificates-0:2023.2.62_v 100% | 168.4 MiB/s | 862.1 KiB |  00m00s
[ 95/155] fedora-repos-rawhide-0:41-0.2 100% |   2.2 MiB/s |   8.9 KiB |  00m00s
[ 96/155] fedora-gpg-keys-0:41-0.2.noar 100% |  21.5 MiB/s | 131.8 KiB |  00m00s
[ 97/155] pcre2-syntax-0:10.43-2.fc41.1 100% |  48.5 MiB/s | 148.9 KiB |  00m00s
[ 98/155] curl-0:8.8.0-1.fc41.x86_64    100% |  73.6 MiB/s | 301.5 KiB |  00m00s
[ 99/155] file-libs-0:5.45-5.fc41.x86_6 100% |  82.8 MiB/s | 763.0 KiB |  00m00s
[100/155] libarchive-0:3.7.4-1.fc41.x86 100% |  66.3 MiB/s | 407.6 KiB |  00m00s
[101/155] elfutils-libs-0:0.191-7.fc41. 100% |  42.0 MiB/s | 258.1 KiB |  00m00s
[102/155] elfutils-debuginfod-client-0: 100% |   7.5 MiB/s |  38.2 KiB |  00m00s
[103/155] libstdc++-0:14.1.1-1.fc41.x86 100% | 172.4 MiB/s | 882.7 KiB |  00m00s
[104/155] libzstd-0:1.5.6-1.fc41.x86_64 100% |  75.4 MiB/s | 308.9 KiB |  00m00s
[105/155] add-determinism-nopython-0:0. 100% |  34.8 MiB/s | 890.6 KiB |  00m00s
[106/155] libgomp-0:14.1.1-1.fc41.x86_6 100% | 113.4 MiB/s | 348.3 KiB |  00m00s
[107/155] lua-libs-0:5.4.6-5.fc40.x86_6 100% |  42.9 MiB/s | 131.9 KiB |  00m00s
[108/155] lz4-libs-0:1.9.4-6.fc40.x86_6 100% |  16.4 MiB/s |  67.2 KiB |  00m00s
[109/155] rpm-sequoia-0:1.6.0-2.fc40.x8 100% | 137.9 MiB/s | 847.5 KiB |  00m00s
[110/155] sqlite-libs-0:3.45.3-1.fc41.x 100% |  98.4 MiB/s | 705.4 KiB |  00m00s
[111/155] libxml2-0:2.12.7-1.fc41.x86_6 100% | 133.8 MiB/s | 685.2 KiB |  00m00s
[112/155] elfutils-default-yama-scope-0 100% |   4.3 MiB/s |  13.3 KiB |  00m00s
[113/155] authselect-libs-0:1.5.0-5.fc4 100% |  71.2 MiB/s | 218.6 KiB |  00m00s
[114/155] pam-0:1.6.1-1.fc41.x86_64     100% | 135.1 MiB/s | 553.5 KiB |  00m00s
[115/155] gdbm-libs-1:1.23-6.fc40.x86_6 100% |  18.3 MiB/s |  56.2 KiB |  00m00s
[116/155] authselect-0:1.5.0-5.fc41.x86 100% |  28.5 MiB/s | 146.2 KiB |  00m00s
[117/155] libnsl2-0:2.0.1-1.fc40.x86_64 100% |  14.4 MiB/s |  29.6 KiB |  00m00s
[118/155] libpwquality-0:1.4.5-9.fc40.x 100% |  39.0 MiB/s | 119.7 KiB |  00m00s
[119/155] libtirpc-0:1.3.4-1.rc3.fc41.x 100% |  30.1 MiB/s |  92.5 KiB |  00m00s
[120/155] cracklib-0:2.9.11-5.fc40.x86_ 100% |  30.1 MiB/s |  92.5 KiB |  00m00s
[121/155] libcom_err-0:1.47.0-5.fc40.x8 100% |   5.0 MiB/s |  25.4 KiB |  00m00s
[122/155] krb5-libs-0:1.21.2-5.fc40.x86 100% | 105.5 MiB/s | 756.1 KiB |  00m00s
[123/155] keyutils-libs-0:1.6.3-3.fc40. 100% |   6.1 MiB/s |  31.5 KiB |  00m00s
[124/155] libverto-0:0.3.2-8.fc40.x86_6 100% |  10.0 MiB/s |  20.5 KiB |  00m00s
[125/155] alternatives-0:1.27-1.fc41.x8 100% |  19.9 MiB/s |  40.7 KiB |  00m00s
[126/155] binutils-gold-0:2.42.50-11.fc 100% |  95.6 MiB/s | 783.1 KiB |  00m00s
[127/155] jansson-0:2.13.1-9.fc40.x86_6 100% |   3.6 MiB/s |  44.2 KiB |  00m00s
[128/155] pkgconf-pkg-config-0:2.1.1-1. 100% |   1.1 MiB/s |   9.9 KiB |  00m00s
[129/155] binutils-0:2.42.50-11.fc41.x8 100% | 255.3 MiB/s |   6.4 MiB |  00m00s
[130/155] pkgconf-0:2.1.1-1.fc41.x86_64 100% |   4.3 MiB/s |  43.9 KiB |  00m00s
[131/155] pkgconf-m4-0:2.1.1-1.fc41.noa 100% |   2.7 MiB/s |  14.1 KiB |  00m00s
[132/155] libpkgconf-0:2.1.1-1.fc41.x86 100% |  18.5 MiB/s |  38.0 KiB |  00m00s
[133/155] gdbm-1:1.23-6.fc40.x86_64     100% |  49.6 MiB/s | 152.5 KiB |  00m00s
[134/155] p11-kit-0:0.25.3-4.fc40.x86_6 100% |  95.7 MiB/s | 489.8 KiB |  00m00s
[135/155] libffi-0:3.4.6-1.fc41.x86_64  100% |  13.0 MiB/s |  40.0 KiB |  00m00s
[136/155] libtasn1-0:4.19.0-6.fc40.x86_ 100% |  24.0 MiB/s |  73.7 KiB |  00m00s
[137/155] fedora-release-0:41-0.10.noar 100% |  10.9 MiB/s |  11.1 KiB |  00m00s
[138/155] p11-kit-trust-0:0.25.3-4.fc40 100% |  42.8 MiB/s | 131.5 KiB |  00m00s
[139/155] xxhash-libs-0:0.8.2-2.fc40.x8 100% |  18.0 MiB/s |  36.9 KiB |  00m00s
[140/155] gmp-1:6.3.0-1.fc41.x86_64     100% | 103.1 MiB/s | 316.8 KiB |  00m00s
[141/155] fedora-release-identity-basic 100% |   5.8 MiB/s |  11.9 KiB |  00m00s
[142/155] libcurl-0:8.8.0-1.fc41.x86_64 100% |  86.7 MiB/s | 355.3 KiB |  00m00s
[143/155] libbrotli-0:1.1.0-3.fc40.x86_ 100% |  66.1 MiB/s | 338.4 KiB |  00m00s
[144/155] libidn2-0:2.3.7-1.fc40.x86_64 100% |  29.0 MiB/s | 118.7 KiB |  00m00s
[145/155] libnghttp2-0:1.62.0-1.fc41.x8 100% |  14.9 MiB/s |  76.5 KiB |  00m00s
[146/155] gdb-minimal-0:14.2-7.fc41.x86 100% | 204.0 MiB/s |   4.3 MiB |  00m00s
[147/155] libpsl-0:0.21.5-3.fc40.x86_64 100% |  10.4 MiB/s |  63.9 KiB |  00m00s
[148/155] libssh-0:0.10.6-6.fc41.x86_64 100% |  51.6 MiB/s | 211.5 KiB |  00m00s
[149/155] publicsuffix-list-dafsa-0:202 100% |  28.4 MiB/s |  58.1 KiB |  00m00s
[150/155] openldap-0:2.6.7-1.fc40.x86_6 100% |  62.1 MiB/s | 254.3 KiB |  00m00s
[151/155] libunistring-0:1.1-7.fc41.x86 100% | 106.5 MiB/s | 545.4 KiB |  00m00s
[152/155] libssh-config-0:0.10.6-6.fc41 100% |   3.0 MiB/s |   9.1 KiB |  00m00s
[153/155] libtool-ltdl-0:2.4.7-10.fc40. 100% |  17.7 MiB/s |  36.2 KiB |  00m00s
[154/155] cyrus-sasl-lib-0:2.1.28-22.fc 100% | 129.1 MiB/s | 793.4 KiB |  00m00s
[155/155] 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) <fedora-41-primary@fedoraproject.org>"
 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) <fedora-41-primary@fedoraproject.org>"
 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) <fedora-40-primary@fedoraproject.org>"
 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 |   5.7 KiB |  00m00s
[  9/157] Installing fedora-release-com 100% |  22.9 MiB/s |  23.5 KiB |  00m00s
[ 10/157] Installing fedora-release-0:4 100% | 121.1 KiB/s | 124.0   B |  00m00s
[ 11/157] Installing setup-0:2.14.5-2.f 100% |  64.4 MiB/s | 725.8 KiB |  00m00s
>>> Running post-install scriptlet: setup-0:2.14.5-2.fc40.noarch
>>> Stop post-install scriptlet: setup-0:2.14.5-2.fc40.noarch
[ 12/157] Installing filesystem-0:3.18- 100% |   3.6 MiB/s | 212.5 KiB |  00m00s
[ 13/157] Installing basesystem-0:11-20 100% |   0.0   B/s | 124.0   B |  00m00s
[ 14/157] Installing libssh-config-0:0. 100% |   0.0   B/s | 816.0   B |  00m00s
[ 15/157] Installing publicsuffix-list- 100% |   0.0   B/s |  68.3 KiB |  00m00s
[ 16/157] Installing pkgconf-m4-0:2.1.1 100% |   0.0   B/s |  14.3 KiB |  00m00s
[ 17/157] Installing pcre2-syntax-0:10. 100% | 245.6 MiB/s | 251.5 KiB |  00m00s
[ 18/157] Installing ncurses-base-0:6.4 100% |  85.8 MiB/s | 351.6 KiB |  00m00s
[ 19/157] Installing glibc-minimal-lang 100% |   0.0   B/s | 124.0   B |  00m00s
[ 20/157] 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 KiB |  00m00s
[ 26/157] Installing bzip2-libs-0:1.0.8 100% |  79.9 MiB/s |  81.8 KiB |  00m00s
[ 27/157] Installing xz-libs-1:5.4.6-3. 100% | 206.0 MiB/s | 210.9 KiB |  00m00s
[ 28/157] Installing popt-0:1.19-6.fc40 100% |  70.1 MiB/s | 143.5 KiB |  00m00s
[ 29/157] Installing readline-0:8.2-8.f 100% | 239.9 MiB/s | 491.4 KiB |  00m00s
[ 30/157] Installing libuuid-0:2.40.1-1 100% |   0.0   B/s |  38.4 KiB |  00m00s
[ 31/157] Installing libstdc++-0:14.1.1 100% | 394.6 MiB/s |   2.8 MiB |  00m00s
[ 32/157] Installing libzstd-0:1.5.6-1. 100% | 385.3 MiB/s | 789.2 KiB |  00m00s
[ 33/157] Installing elfutils-libelf-0: 100% | 389.8 MiB/s |   1.2 MiB |  00m00s
[ 34/157] Installing libblkid-0:2.40.1- 100% | 253.6 MiB/s | 259.7 KiB |  00m00s
[ 35/157] Installing libattr-0:2.5.2-3. 100% |   0.0   B/s |  29.5 KiB |  00m00s
[ 36/157] Installing libacl-0:2.3.2-1.f 100% |   0.0   B/s |  40.8 KiB |  00m00s
[ 37/157] Installing libxcrypt-0:4.4.36 100% | 259.3 MiB/s | 265.5 KiB |  00m00s
[ 38/157] Installing gmp-1:6.3.0-1.fc41 100% | 393.4 MiB/s | 805.6 KiB |  00m00s
[ 39/157] Installing libeconf-0:0.6.2-1 100% |   0.0   B/s |  59.6 KiB |  00m00s
[ 40/157] Installing gdbm-libs-1:1.23-6 100% | 120.7 MiB/s | 123.6 KiB |  00m00s
[ 41/157] Installing mpfr-0:4.2.1-4.fc4 100% | 270.1 MiB/s | 829.7 KiB |  00m00s
[ 42/157] Installing gawk-0:5.3.0-3.fc4 100% | 345.6 MiB/s |   1.7 MiB |  00m00s
[ 43/157] Installing dwz-0:0.15-6.fc40. 100% | 285.5 MiB/s | 292.3 KiB |  00m00s
[ 44/157] Installing unzip-0:6.0-63.fc4 100% | 188.6 MiB/s | 386.3 KiB |  00m00s
[ 45/157] Installing file-libs-0:5.45-5 100% | 709.3 MiB/s |   9.9 MiB |  00m00s
[ 46/157] Installing file-0:5.45-5.fc41 100% | 102.6 MiB/s | 105.0 KiB |  00m00s
[ 47/157] Installing pcre2-0:10.43-2.fc 100% | 319.8 MiB/s | 654.9 KiB |  00m00s
[ 48/157] Installing grep-0:3.11-8.fc41 100% | 249.8 MiB/s |   1.0 MiB |  00m00s
[ 49/157] Installing xz-1:5.4.6-3.fc41. 100% | 286.1 MiB/s |   2.0 MiB |  00m00s
[ 50/157] Installing libcap-ng-0:0.8.5- 100% |  69.3 MiB/s |  71.0 KiB |  00m00s
[ 51/157] Installing audit-libs-0:4.0.1 100% | 321.6 MiB/s | 329.3 KiB |  00m00s
[ 52/157] Installing pam-libs-0:1.6.1-1 100% | 134.2 MiB/s | 137.4 KiB |  00m00s
[ 53/157] Installing libcap-0:2.70-1.fc 100% | 110.0 MiB/s | 225.2 KiB |  00m00s
[ 54/157] Installing systemd-libs-0:256 100% | 404.5 MiB/s |   2.0 MiB |  00m00s
[ 55/157] Installing libsmartcols-0:2.4 100% | 177.3 MiB/s | 181.5 KiB |  00m00s
[ 56/157] Installing libsepol-0:3.6-3.f 100% | 392.1 MiB/s | 803.0 KiB |  00m00s
[ 57/157] Installing libselinux-0:3.6-4 100% | 170.2 MiB/s | 174.3 KiB |  00m00s
[ 58/157] Installing sed-0:4.9-1.fc40.x 100% | 212.3 MiB/s | 869.7 KiB |  00m00s
[ 59/157] Installing findutils-1:4.9.0- 100% | 293.2 MiB/s |   1.5 MiB |  00m00s
[ 60/157] Installing libmount-0:2.40.1- 100% | 344.6 MiB/s | 352.9 KiB |  00m00s
[ 61/157] Installing lua-libs-0:5.4.6-5 100% | 275.7 MiB/s | 282.3 KiB |  00m00s
[ 62/157] Installing lz4-libs-0:1.9.4-6 100% | 127.4 MiB/s | 130.5 KiB |  00m00s
[ 63/157] Installing libcom_err-0:1.47. 100% |  66.7 MiB/s |  68.3 KiB |  00m00s
[ 64/157] Installing alternatives-0:1.2 100% |  66.4 MiB/s |  68.0 KiB |  00m00s
[ 65/157] Installing jansson-0:2.13.1-9 100% |  87.6 MiB/s |  89.7 KiB |  00m00s
[ 66/157] Installing libtasn1-0:4.19.0- 100% | 173.3 MiB/s | 177.5 KiB |  00m00s
[ 67/157] Installing libunistring-0:1.1 100% | 432.7 MiB/s |   1.7 MiB |  00m00s
[ 68/157] Installing libidn2-0:2.3.7-1. 100% | 163.6 MiB/s | 335.0 KiB |  00m00s
[ 69/157] Installing libpsl-0:0.21.5-3. 100% |  79.7 MiB/s |  81.6 KiB |  00m00s
[ 70/157] Installing zstd-0:1.5.6-1.fc4 100% | 419.0 MiB/s |   1.7 MiB |  00m00s
[ 71/157] Installing util-linux-core-0: 100% | 247.5 MiB/s |   1.5 MiB |  00m00s
[ 72/157] Installing tar-2:1.35-3.fc40. 100% | 421.5 MiB/s |   3.0 MiB |  00m00s
[ 73/157] Installing libsemanage-0:3.6- 100% | 144.2 MiB/s | 295.3 KiB |  00m00s
[ 74/157] Installing shadow-utils-2:4.1 100% | 154.5 MiB/s |   4.2 MiB |  00m00s
>>> Running pre-install scriptlet: libutempter-0:1.2.1-13.fc40.x86_64
>>> Stop pre-install scriptlet: libutempter-0:1.2.1-13.fc40.x86_64
[ 75/157] Installing libutempter-0:1.2. 100% |  58.3 MiB/s |  59.7 KiB |  00m00s
[ 76/157] Installing zip-0:3.0-40.fc40. 100% | 230.2 MiB/s | 707.1 KiB |  00m00s
[ 77/157] Installing gdbm-1:1.23-6.fc40 100% | 227.4 MiB/s | 465.8 KiB |  00m00s
[ 78/157] Installing cyrus-sasl-lib-0:2 100% | 381.8 MiB/s |   2.3 MiB |  00m00s
[ 79/157] Installing libfdisk-0:2.40.1- 100% | 355.4 MiB/s | 363.9 KiB |  00m00s
[ 80/157] Installing add-determinism-no 100% | 420.6 MiB/s |   2.5 MiB |  00m00s
[ 81/157] Installing build-reproducibil 100% |   0.0   B/s |   1.0 KiB |  00m00s
[ 82/157] Installing libxml2-0:2.12.7-1 100% | 340.1 MiB/s |   1.7 MiB |  00m00s
[ 83/157] Installing bzip2-0:1.0.8-18.f 100% |  93.9 MiB/s |  96.2 KiB |  00m00s
[ 84/157] Installing sqlite-libs-0:3.45 100% | 351.3 MiB/s |   1.4 MiB |  00m00s
[ 85/157] Installing ed-0:1.20.2-1.fc41 100% | 145.7 MiB/s | 149.2 KiB |  00m00s
[ 86/157] Installing patch-0:2.7.6-24.f 100% | 258.1 MiB/s | 264.3 KiB |  00m00s
[ 87/157] Installing elfutils-default-y 100% | 340.5 KiB/s |   2.0 KiB |  00m00s
>>> Running post-install scriptlet: elfutils-default-yama-scope-0:0.191-7.fc41.n
>>> Stop post-install scriptlet: elfutils-default-yama-scope-0:0.191-7.fc41.noar
[ 88/157] Installing cpio-0:2.15-1.fc40 100% | 274.9 MiB/s |   1.1 MiB |  00m00s
[ 89/157] Installing diffutils-0:3.10-5 100% | 317.2 MiB/s |   1.6 MiB |  00m00s
[ 90/157] Installing libgomp-0:14.1.1-1 100% | 254.3 MiB/s | 520.9 KiB |  00m00s
[ 91/157] Installing keyutils-libs-0:1. 100% |   0.0   B/s |  55.8 KiB |  00m00s
[ 92/157] Installing libverto-0:0.3.2-8 100% |   0.0   B/s |  31.3 KiB |  00m00s
[ 93/157] Installing libpkgconf-0:2.1.1 100% |  73.6 MiB/s |  75.3 KiB |  00m00s
[ 94/157] Installing pkgconf-0:2.1.1-1. 100% |  83.4 MiB/s |  85.4 KiB |  00m00s
[ 95/157] Installing pkgconf-pkg-config 100% |   0.0   B/s |   1.8 KiB |  00m00s
[ 96/157] Installing libffi-0:3.4.6-1.f 100% |  81.8 MiB/s |  83.8 KiB |  00m00s
[ 97/157] Installing p11-kit-0:0.25.3-4 100% | 274.3 MiB/s |   2.2 MiB |  00m00s
[ 98/157] Installing p11-kit-trust-0:0. 100% |  54.8 MiB/s | 393.1 KiB |  00m00s
>>> Running post-install scriptlet: p11-kit-trust-0:0.25.3-4.fc40.x86_64
>>> Stop post-install scriptlet: p11-kit-trust-0:0.25.3-4.fc40.x86_64
[ 99/157] Installing xxhash-libs-0:0.8. 100% |  87.8 MiB/s |  89.9 KiB |  00m00s
[100/157] Installing libbrotli-0:1.1.0- 100% | 270.8 MiB/s | 831.8 KiB |  00m00s
[101/157] Installing libnghttp2-0:1.62. 100% | 163.3 MiB/s | 167.2 KiB |  00m00s
[102/157] Installing libtool-ltdl-0:2.4 100% |   0.0   B/s |  67.3 KiB |  00m00s
[103/157] Installing rust-srpm-macros-0 100% |   0.0   B/s |   5.6 KiB |  00m00s
[104/157] Installing qt6-srpm-macros-0: 100% |   0.0   B/s | 732.0   B |  00m00s
[105/157] Installing qt5-srpm-macros-0: 100% |   0.0   B/s | 768.0   B |  00m00s
[106/157] Installing perl-srpm-macros-0 100% |   0.0   B/s |   1.1 KiB |  00m00s
[107/157] Installing package-notes-srpm 100% |   0.0   B/s |   2.0 KiB |  00m00s
[108/157] Installing openblas-srpm-macr 100% |   0.0   B/s | 392.0   B |  00m00s
[109/157] Installing ocaml-srpm-macros- 100% |   0.0   B/s |   2.2 KiB |  00m00s
[110/157] Installing kernel-srpm-macros 100% |   0.0   B/s |   2.3 KiB |  00m00s
[111/157] Installing gnat-srpm-macros-0 100% |   0.0   B/s |   1.3 KiB |  00m00s
[112/157] Installing ghc-srpm-macros-0: 100% |   0.0   B/s |   1.0 KiB |  00m00s
[113/157] Installing fpc-srpm-macros-0: 100% |   0.0   B/s | 420.0   B |  00m00s
[114/157] Installing ansible-srpm-macro 100% |  35.4 MiB/s |  36.2 KiB |  00m00s
[115/157] Installing coreutils-common-0 100% | 430.4 MiB/s |  11.2 MiB |  00m00s
[116/157] Installing openssl-libs-1:3.2 100% | 458.6 MiB/s |   7.8 MiB |  00m00s
[117/157] Installing coreutils-0:9.5-1. 100% | 294.2 MiB/s |   5.6 MiB |  00m00s
>>> Running pre-install scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.fc40.n
>>> Stop pre-install scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.fc40.noar
[118/157] Installing ca-certificates-0: 100% |   4.3 MiB/s |   2.3 MiB |  00m01s
>>> Running post-install scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.fc40.
>>> Stop post-install scriptlet: ca-certificates-0:2023.2.62_v7.0.401-6.fc40.noa
[119/157] Installing krb5-libs-0:1.21.2 100% | 286.8 MiB/s |   2.3 MiB |  00m00s
[120/157] Installing libtirpc-0:1.3.4-1 100% | 199.8 MiB/s | 204.6 KiB |  00m00s
[121/157] Installing gzip-0:1.13-1.fc40 100% | 190.7 MiB/s | 390.6 KiB |  00m00s
[122/157] Installing authselect-libs-0: 100% | 203.4 MiB/s | 833.2 KiB |  00m00s
[123/157] Installing libarchive-0:3.7.4 100% | 298.4 MiB/s | 916.6 KiB |  00m00s
[124/157] Installing authselect-0:1.5.0 100% |  77.1 MiB/s | 157.9 KiB |  00m00s
[125/157] Installing cracklib-0:2.9.11- 100% |  81.5 MiB/s | 250.3 KiB |  00m00s
[126/157] Installing libpwquality-0:1.4 100% | 105.0 MiB/s | 430.1 KiB |  00m00s
[127/157] Installing libnsl2-0:2.0.1-1. 100% |  57.7 MiB/s |  59.0 KiB |  00m00s
[128/157] Installing pam-0:1.6.1-1.fc41 100% | 165.0 MiB/s |   1.8 MiB |  00m00s
[129/157] Installing libssh-0:0.10.6-6. 100% | 251.7 MiB/s | 515.4 KiB |  00m00s
[130/157] Installing rpm-sequoia-0:1.6. 100% | 371.5 MiB/s |   2.2 MiB |  00m00s
[131/157] Installing rpm-libs-0:4.19.1. 100% | 231.6 MiB/s | 711.5 KiB |  00m00s
[132/157] Installing libevent-0:2.1.12- 100% | 292.8 MiB/s | 899.4 KiB |  00m00s
[133/157] Installing openldap-0:2.6.7-1 100% | 312.0 MiB/s | 638.9 KiB |  00m00s
[134/157] Installing libcurl-0:8.8.0-1. 100% | 262.6 MiB/s | 806.8 KiB |  00m00s
[135/157] Installing elfutils-libs-0:0. 100% | 316.4 MiB/s | 648.0 KiB |  00m00s
[136/157] Installing elfutils-debuginfo 100% |  65.3 MiB/s |  66.9 KiB |  00m00s
[137/157] Installing binutils-gold-0:2. 100% | 156.2 MiB/s |   2.0 MiB |  00m00s
>>> Running post-install scriptlet: binutils-gold-0:2.42.50-11.fc41.x86_64
>>> Stop post-install scriptlet: binutils-gold-0:2.42.50-11.fc41.x86_64
[138/157] Installing binutils-0:2.42.50 100% | 404.7 MiB/s |  27.5 MiB |  00m00s
>>> Running post-install scriptlet: binutils-0:2.42.50-11.fc41.x86_64
>>> Stop post-install scriptlet: binutils-0:2.42.50-11.fc41.x86_64
[139/157] Installing elfutils-0:0.191-7 100% | 364.6 MiB/s |   2.6 MiB |  00m00s
[140/157] Installing gdb-minimal-0:14.2 100% | 436.5 MiB/s |  12.7 MiB |  00m00s
[141/157] Installing debugedit-0:5.0-16 100% | 197.3 MiB/s | 202.0 KiB |  00m00s
[142/157] Installing rpm-build-libs-0:4 100% | 194.6 MiB/s | 199.2 KiB |  00m00s
[143/157] Installing curl-0:8.8.0-1.fc4 100% |  72.9 MiB/s | 746.2 KiB |  00m00s
>>> Running pre-install scriptlet: rpm-0:4.19.1.1-2.fc41.x86_64
>>> Stop pre-install scriptlet: rpm-0:4.19.1.1-2.fc41.x86_64
[144/157] Installing rpm-0:4.19.1.1-2.f 100% | 184.4 MiB/s |   2.4 MiB |  00m00s
[145/157] Installing efi-srpm-macros-0: 100% |   0.0   B/s |  41.2 KiB |  00m00s
[146/157] Installing lua-srpm-macros-0: 100% |   0.0   B/s |   1.9 KiB |  00m00s
[147/157] Installing zig-srpm-macros-0: 100% |   0.0   B/s |   1.7 KiB |  00m00s
[148/157] Installing fonts-srpm-macros- 100% |   0.0   B/s |  56.5 KiB |  00m00s
[149/157] Installing forge-srpm-macros- 100% |   0.0   B/s |  40.3 KiB |  00m00s
[150/157] Installing go-srpm-macros-0:3 100% |   0.0   B/s |  62.0 KiB |  00m00s
[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).
[  1/229] R-CRAN-Formula-0:1.2.5-1.fc41 100% |  11.8 MiB/s | 168.7 KiB |  00m00s
[  2/229] R-CRAN-RcppEigen-0:0.3.4.0.0- 100% | 143.4 MiB/s |   1.4 MiB |  00m00s
[  3/229] R-CRAN-RcppParallel-0:5.1.7-1 100% |  79.8 MiB/s | 326.8 KiB |  00m00s
[  4/229] R-CRAN-StanHeaders-0:2.32.8-1 100% | 119.3 MiB/s |   1.6 MiB |  00m00s
[  5/229] R-CRAN-abind-0:1.4.5-3.fc41.c 100% |  25.3 MiB/s |  77.7 KiB |  00m00s
[  6/229] R-CRAN-assertthat-0:0.2.1-3.f 100% |  22.5 MiB/s |  69.2 KiB |  00m00s
[  7/229] R-CRAN-BH-0:1.84.0.0-1.fc41.c 100% | 137.6 MiB/s |   9.8 MiB |  00m00s
[  8/229] R-CRAN-Rcpp-0:1.0.12-1.fc41.c 100% |  25.5 MiB/s |   2.0 MiB |  00m00s
[  9/229] R-CRAN-bayesplot-0:1.11.1-1.f 100% | 158.5 MiB/s |   5.1 MiB |  00m00s
[ 10/229] R-CRAN-checkmate-0:2.3.1-1.fc 100% | 104.6 MiB/s | 749.9 KiB |  00m00s
[ 11/229] R-CRAN-matrixStats-0:1.3.0-1. 100% |  50.0 MiB/s | 512.0 KiB |  00m00s
[ 12/229] R-CRAN-dplyr-0:1.1.4-1.fc41.c 100% | 122.1 MiB/s |   1.5 MiB |  00m00s
[ 13/229] R-CRAN-mvtnorm-0:1.2.5-1.fc41 100% | 124.5 MiB/s | 764.9 KiB |  00m00s
[ 14/229] R-CRAN-rlang-0:1.1.3-1.fc41.c 100% | 138.0 MiB/s |   1.7 MiB |  00m00s
[ 15/229] R-CRAN-rstan-0:2.32.6-1.fc41. 100% | 144.9 MiB/s |   2.0 MiB |  00m00s
[ 16/229] R-CRAN-rstantools-0:2.4.0-1.f 100% |  25.1 MiB/s | 179.7 KiB |  00m00s
[ 17/229] R-devel-0:4.4.0-1.fc41~bootst 100% |   2.6 MiB/s |  10.7 KiB |  00m00s
[ 18/229] R-littler-0:0.3.19-4.fc41.x86 100% |   7.7 MiB/s |  71.0 KiB |  00m00s
[ 19/229] flexiblas-netlib-0:3.4.2-1.fc 100% | 263.5 MiB/s |   3.2 MiB |  00m00s
[ 20/229] tbb-0:2021.11.0-5.fc40.x86_64 100% | 159.5 MiB/s | 163.3 KiB |  00m00s
[ 21/229] R-CRAN-ggridges-0:0.5.6-1.fc4 100% | 208.2 MiB/s |   2.1 MiB |  00m00s
[ 22/229] R-CRAN-glue-0:1.7.0-1.fc41.co 100% |  40.6 MiB/s | 166.3 KiB |  00m00s
[ 23/229] R-CRAN-posterior-0:1.5.0-1.fc 100% |  99.2 MiB/s |   1.0 MiB |  00m00s
[ 24/229] R-CRAN-reshape2-0:1.4.4-3.fc4 100% |  25.2 MiB/s | 129.1 KiB |  00m00s
[ 25/229] R-CRAN-tibble-0:3.2.1-1.fc41. 100% | 102.7 MiB/s | 630.8 KiB |  00m00s
[ 26/229] R-CRAN-tidyselect-0:1.2.1-1.f 100% |  74.9 MiB/s | 230.1 KiB |  00m00s
[ 27/229] R-CRAN-backports-0:1.4.1-1.fc 100% |  29.4 MiB/s | 120.5 KiB |  00m00s
[ 28/229] R-CRAN-R6-0:2.5.1-1.fc41.copr 100% |  23.3 MiB/s |  95.5 KiB |  00m00s
[ 29/229] R-CRAN-cli-0:3.6.2-1.fc41.cop 100% | 146.8 MiB/s |   1.3 MiB |  00m00s
[ 30/229] R-CRAN-generics-0:0.1.3-1.fc4 100% |  20.2 MiB/s | 103.7 KiB |  00m00s
[ 31/229] R-CRAN-lifecycle-0:1.0.4-1.fc 100% |  21.2 MiB/s | 130.2 KiB |  00m00s
[ 32/229] R-CRAN-pillar-0:1.9.0-1.fc41. 100% |  67.6 MiB/s | 623.3 KiB |  00m00s
[ 33/229] R-CRAN-vctrs-0:0.6.5-1.fc41.c 100% |  98.3 MiB/s |   1.3 MiB |  00m00s
[ 34/229] R-CRAN-MASS-0:7.3.60.2-1.fc41 100% | 107.2 MiB/s |   1.2 MiB |  00m00s
[ 35/229] R-CRAN-gtable-0:0.3.5-1.fc41. 100% |  45.0 MiB/s | 230.3 KiB |  00m00s
[ 36/229] R-CRAN-isoband-0:0.2.7-1.fc41 100% | 104.1 MiB/s |   1.6 MiB |  00m00s
[ 37/229] R-CRAN-ggplot2-0:3.5.1-1.fc41 100% |  21.8 MiB/s |   4.7 MiB |  00m00s
[ 38/229] R-CRAN-mgcv-0:1.9.1-1.fc41.co 100% | 108.2 MiB/s |   3.2 MiB |  00m00s
[ 39/229] 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 |  00m00s
[ 52/229] libXt-0:1.3.0-3.fc40.x86_64   100% |  86.7 MiB/s | 177.5 KiB |  00m00s
[ 53/229] libjpeg-turbo-0:3.0.2-2.fc41. 100% |  73.7 MiB/s | 226.4 KiB |  00m00s
[ 54/229] libpng-2:1.6.40-3.fc40.x86_64 100% |  58.6 MiB/s | 119.9 KiB |  00m00s
[ 55/229] libtiff-0:4.6.0-2.fc40.x86_64 100% |  54.1 MiB/s | 332.4 KiB |  00m00s
[ 56/229] pango-0:1.52.2-1.fc41.x86_64  100% |  67.8 MiB/s | 347.0 KiB |  00m00s
[ 57/229] tcl-1:8.6.14-1.fc41.x86_64    100% | 137.8 MiB/s |   1.1 MiB |  00m00s
[ 58/229] R-core-0:4.4.0-1.fc41~bootstr 100% | 190.6 MiB/s |  62.5 MiB |  00m00s
[ 59/229] tk-1:8.6.14-1.fc41.x86_64     100% |  25.7 MiB/s |   1.6 MiB |  00m00s
[ 60/229] libicu-0:74.2-1.fc40.x86_64   100% | 102.3 MiB/s |  10.4 MiB |  00m00s
[ 61/229] tre-0:0.8.0-43.20140228gitc2f 100% |   4.2 MiB/s |  43.5 KiB |  00m00s
[ 62/229] xdg-utils-0:1.2.1-1.fc41.noar 100% |   9.1 MiB/s |  83.6 KiB |  00m00s
[ 63/229] libgfortran-0:14.1.1-1.fc41.x 100% | 303.7 MiB/s | 932.9 KiB |  00m00s
[ 64/229] flexiblas-0:3.4.2-1.fc41.x86_ 100% |   6.1 MiB/s |  25.1 KiB |  00m00s
[ 65/229] flexiblas-openblas-openmp-0:3 100% |   5.7 MiB/s |  17.6 KiB |  00m00s
[ 66/229] libquadmath-0:14.1.1-1.fc41.x 100% |  96.1 MiB/s | 196.9 KiB |  00m00s
[ 67/229] R-CRAN-distributional-0:0.4.0 100% | 144.5 MiB/s | 443.8 KiB |  00m00s
[ 68/229] R-CRAN-tensorA-0:0.36.2.1-1.f 100% |  63.5 MiB/s | 260.2 KiB |  00m00s
[ 69/229] R-CRAN-plyr-0:1.8.9-1.fc41.co 100% |  90.2 MiB/s | 831.1 KiB |  00m00s
[ 70/229] R-CRAN-stringr-0:1.5.1-1.fc41 100% |  38.8 MiB/s | 318.0 KiB |  00m00s
[ 71/229] R-CRAN-fansi-0:1.0.6-1.fc41.c 100% |  42.6 MiB/s | 349.2 KiB |  00m00s
[ 72/229] R-CRAN-pkgconfig-0:2.0.3-3.fc 100% |  14.6 MiB/s |  30.0 KiB |  00m00s
[ 73/229] R-CRAN-utf8-0:1.2.4-1.fc41.co 100% |  73.3 MiB/s | 150.1 KiB |  00m00s
[ 74/229] R-CRAN-RColorBrewer-0:1.1.3-1 100% |   7.7 MiB/s |  62.7 KiB |  00m00s
[ 75/229] R-CRAN-nlme-0:3.1.164-1.fc41. 100% | 114.4 MiB/s |   2.4 MiB |  00m00s
[ 76/229] R-CRAN-farver-0:2.1.2-1.fc41. 100% |  88.8 MiB/s |   1.3 MiB |  00m00s
[ 77/229] R-CRAN-Matrix-0:1.7.0-1.fc41. 100% | 133.9 MiB/s |   4.3 MiB |  00m00s
[ 78/229] R-CRAN-labeling-0:0.4.3-1.fc4 100% |   9.3 MiB/s |  76.2 KiB |  00m00s
[ 79/229] R-CRAN-munsell-0:0.5.1-1.fc41 100% |  40.9 MiB/s | 251.0 KiB |  00m00s
[ 80/229] R-CRAN-callr-0:3.7.6-1.fc41.c 100% |  86.2 MiB/s | 441.2 KiB |  00m00s
[ 81/229] R-CRAN-viridisLite-0:0.4.2-1. 100% | 156.1 MiB/s |   1.2 MiB |  00m00s
[ 82/229] R-CRAN-processx-0:3.8.4-1.fc4 100% |  86.9 MiB/s | 355.9 KiB |  00m00s
[ 83/229] fontconfig-0:2.15.0-5.fc41.x8 100% | 131.5 MiB/s | 269.3 KiB |  00m00s
[ 84/229] R-CRAN-jsonlite-0:1.8.8-1.fc4 100% |  56.4 MiB/s | 635.7 KiB |  00m00s
[ 85/229] libXext-0:1.3.6-1.fc40.x86_64 100% |  38.0 MiB/s |  38.9 KiB |  00m00s
[ 86/229] libXrender-0:0.9.11-6.fc40.x8 100% |  26.7 MiB/s |  27.4 KiB |  00m00s
[ 87/229] libxcb-0:1.17.0-1.fc41.x86_64 100% | 116.7 MiB/s | 239.1 KiB |  00m00s
[ 88/229] pixman-0:0.43.4-1.fc41.x86_64 100% | 143.2 MiB/s | 293.3 KiB |  00m00s
[ 89/229] gnutls-0:3.8.5-2.fc41.x86_64  100% | 276.1 MiB/s |   1.1 MiB |  00m00s
[ 90/229] 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
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[102/229] libthai-0:0.1.29-8.fc40.x86_6 100% |  69.6 MiB/s | 213.8 KiB |  00m00s
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[106/229] openblas-openmp-0:0.3.26-4.fc 100% | 240.9 MiB/s |   5.1 MiB |  00m00s
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[112/229] libXau-0:1.0.11-6.fc40.x86_64 100% |  31.0 MiB/s |  31.7 KiB |  00m00s
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[116/229] abattis-cantarell-vf-fonts-0: 100% | 117.5 MiB/s | 120.3 KiB |  00m00s
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[121/229] make-1:4.4.1-6.fc40.x86_64    100% | 286.9 MiB/s | 587.6 KiB |  00m00s
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[124/229] guile30-0:3.0.9-1.fc41.x86_64 100% | 332.3 MiB/s |   8.3 MiB |  00m00s
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[129/229] libXtst-0:1.2.4-6.fc40.x86_64 100% |   6.7 MiB/s |  20.4 KiB |  00m00s
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[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
[154/229] libX11-devel-0:1.8.9-1.fc41.x 100% |  37.7 MiB/s |   1.0 MiB |  00m00s
[155/229] libX11-xcb-0:1.8.9-1.fc41.x86 100% | 905.6 KiB/s |  11.8 KiB |  00m00s
[156/229] gcc-gfortran-0:14.1.1-1.fc41. 100% | 141.1 MiB/s |  13.4 MiB |  00m00s
[157/229] xorg-x11-proto-devel-0:2024.1 100% |  18.3 MiB/s | 300.5 KiB |  00m00s
[158/229] libicu-devel-0:74.2-1.fc40.x8 100% |  53.4 MiB/s | 929.9 KiB |  00m00s
[159/229] libtirpc-devel-0:1.3.4-1.rc3. 100% |  40.4 MiB/s | 124.3 KiB |  00m00s
[160/229] pcre2-utf16-0:10.43-2.fc41.1. 100% |  72.3 MiB/s | 222.0 KiB |  00m00s
[161/229] pcre2-utf32-0:10.43-2.fc41.1. 100% |  68.2 MiB/s | 209.5 KiB |  00m00s
[162/229] pcre2-devel-0:10.43-2.fc41.1. 100% |  84.5 MiB/s | 519.4 KiB |  00m00s
[163/229] tre-devel-0:0.8.0-43.20140228 100% |   3.9 MiB/s |  11.8 KiB |  00m00s
[164/229] tcl-devel-1:8.6.14-1.fc41.x86 100% |  23.7 MiB/s | 170.1 KiB |  00m00s
[165/229] tk-devel-1:8.6.14-1.fc41.x86_ 100% |  52.8 MiB/s | 541.1 KiB |  00m00s
[166/229] xz-devel-1:5.4.6-3.fc41.x86_6 100% |  13.1 MiB/s |  67.2 KiB |  00m00s
[167/229] zlib-ng-compat-devel-0:2.1.6- 100% |   5.9 MiB/s |  36.1 KiB |  00m00s
[168/229] R-CRAN-magrittr-0:2.0.3-1.fc4 100% |  72.5 MiB/s | 222.7 KiB |  00m00s
[169/229] libRmath-0:4.4.0-1.fc41~boots 100% |  30.2 MiB/s | 123.7 KiB |  00m00s
[170/229] tbb-devel-0:2021.11.0-5.fc40. 100% |  78.1 MiB/s | 240.0 KiB |  00m00s
[171/229] tbb-bind-0:2021.11.0-5.fc40.x 100% |   4.6 MiB/s |  18.9 KiB |  00m00s
[172/229] cmake-filesystem-0:3.28.3-4.f 100% |   3.5 MiB/s |  17.9 KiB |  00m00s
[173/229] openblas-0:0.3.26-4.fc40.x86_ 100% |   9.4 MiB/s |  38.6 KiB |  00m00s
[174/229] libXft-devel-0:2.3.8-6.fc40.x 100% |   8.2 MiB/s |  50.2 KiB |  00m00s
[175/229] gettext-0:0.22.5-2.fc41.x86_6 100% | 180.3 MiB/s |   1.1 MiB |  00m00s
[176/229] fontconfig-devel-0:2.15.0-5.f 100% |  17.9 MiB/s | 164.6 KiB |  00m00s
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[178/229] gettext-runtime-0:0.22.5-2.fc 100% |  23.9 MiB/s | 122.6 KiB |  00m00s
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[183/229] cups-libs-1:2.4.8-3.fc41.x86_ 100% |  63.2 MiB/s | 259.0 KiB |  00m00s
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[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
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[205/229] python3-0:3.12.3-2.fc41.x86_6 100% |   6.7 MiB/s |  27.2 KiB |  00m00s
[206/229] add-determinism-0:0.2.0-8.fc4 100% |  44.2 MiB/s | 905.9 KiB |  00m00s
[207/229] expat-0:2.6.2-1.fc41.x86_64   100% |  22.1 MiB/s | 113.2 KiB |  00m00s
[208/229] libb2-0:0.98.1-11.fc40.x86_64 100% |   5.0 MiB/s |  25.5 KiB |  00m00s
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[211/229] mpdecimal-0:2.5.1-9.fc40.x86_ 100% |   8.7 MiB/s |  88.6 KiB |  00m00s
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[213/229] tzdata-0:2024a-7.fc41.noarch  100% | 174.7 MiB/s | 715.7 KiB |  00m00s
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[215/229] lua-0:5.4.6-5.fc40.x86_64     100% |  37.3 MiB/s | 190.8 KiB |  00m00s
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[218/229] python3-packaging-0:24.0-1.fc 100% |  41.1 MiB/s | 126.2 KiB |  00m00s
[219/229] kernel-headers-0:6.9.0-64.fc4 100% | 227.7 MiB/s |   1.6 MiB |  00m00s
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[222/229] libffi-devel-0:3.4.6-1.fc41.x 100% |   9.3 MiB/s |  28.7 KiB |  00m00s
[223/229] libmount-devel-0:2.40.1-1.fc4 100% |   8.8 MiB/s |  27.1 KiB |  00m00s
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[227/229] libXext-devel-0:1.3.6-1.fc40. 100% |  14.0 MiB/s |  85.8 KiB |  00m00s
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[229/229] libblkid-devel-0:2.40.1-1.fc4 100% |   8.5 MiB/s |  26.1 KiB |  00m00s
--------------------------------------------------------------------------------
[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
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[  6/231] Installing libgfortran-0:14.1 100% | 420.4 MiB/s |   2.9 MiB |  00m00s
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[  8/231] Installing libmpc-0:1.3.1-5.f 100% | 162.3 MiB/s | 166.2 KiB |  00m00s
[  9/231] Installing libquadmath-0:14.1 100% | 319.5 MiB/s | 327.2 KiB |  00m00s
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[ 11/231] Installing libicu-0:74.2-1.fc 100% | 436.8 MiB/s |  34.9 MiB |  00m00s
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[ 13/231] Installing fonts-filesystem-1 100% | 769.5 KiB/s | 788.0   B |  00m00s
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[ 23/231] Installing xz-devel-1:5.4.6-3 100% | 253.8 MiB/s | 259.9 KiB |  00m00s
[ 24/231] Installing bzip2-devel-0:1.0. 100% | 303.5 MiB/s | 310.7 KiB |  00m00s
[ 25/231] Installing graphite2-0:1.3.14 100% | 189.6 MiB/s | 194.2 KiB |  00m00s
[ 26/231] Installing libXau-0:1.0.11-6. 100% |  66.8 MiB/s |  68.4 KiB |  00m00s
[ 27/231] Installing libxcb-0:1.17.0-1. 100% | 279.1 MiB/s |   1.1 MiB |  00m00s
[ 28/231] Installing libICE-0:1.1.1-3.f 100% | 178.3 MiB/s | 182.6 KiB |  00m00s
[ 29/231] Installing pixman-0:0.43.4-1. 100% | 347.3 MiB/s | 711.2 KiB |  00m00s
[ 30/231] Installing libjpeg-turbo-0:3. 100% | 378.2 MiB/s | 774.6 KiB |  00m00s
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[ 32/231] Installing libSM-0:1.2.4-3.fc 100% |  96.3 MiB/s |  98.6 KiB |  00m00s
[ 33/231] Installing libXau-devel-0:1.0 100% |   1.6 MiB/s |   8.2 KiB |  00m00s
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[ 35/231] Installing graphite2-devel-0: 100% |  49.4 MiB/s |  50.6 KiB |  00m00s
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[ 55/231] Installing lua-0:5.4.6-5.fc40 100% |  97.8 MiB/s | 600.8 KiB |  00m00s
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[ 60/231] Installing expat-0:2.6.2-1.fc 100% |  46.0 MiB/s | 282.9 KiB |  00m00s
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>>> Running post-install scriptlet: nss-0:3.99.0-1.fc41.x86_64
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[ 98/231] Installing make-1:4.4.1-6.fc4 100% | 300.0 MiB/s |   1.8 MiB |  00m00s
[ 99/231] Installing gcc-0:14.1.1-1.fc4 100% | 466.5 MiB/s | 104.0 MiB |  00m00s
>>> Running trigger-install scriptlet: redhat-rpm-config-0:290-1.fc41.noarch
>>> Stop trigger-install scriptlet: redhat-rpm-config-0:290-1.fc41.noarch
[100/231] Installing gcc-c++-0:14.1.1-1 100% | 433.1 MiB/s |  38.1 MiB |  00m00s
[101/231] Installing libquadmath-devel- 100% |  22.7 MiB/s |  23.3 KiB |  00m00s
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[109/231] Installing nettle-0:3.9.1-6.f 100% | 258.2 MiB/s | 793.3 KiB |  00m00s
[110/231] Installing gnutls-0:3.8.5-2.f 100% | 355.5 MiB/s |   3.2 MiB |  00m00s
[111/231] Installing glib2-0:2.80.2-1.f 100% | 429.4 MiB/s |  14.6 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
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[131/231] Installing harfbuzz-0:8.4.0-1 100% | 376.3 MiB/s |   2.6 MiB |  00m00s
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>>> Running post-install scriptlet: fontconfig-0:2.15.0-5.fc41.x86_64
>>> Stop post-install scriptlet: fontconfig-0:2.15.0-5.fc41.x86_64
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>>> Running pre-install scriptlet: tk-1:8.6.14-1.fc41.x86_64
>>> Stop pre-install scriptlet: tk-1:8.6.14-1.fc41.x86_64
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[161/231] Installing R-CRAN-nlme-0:3.1. 100% | 216.7 MiB/s |   3.9 MiB |  00m00s
[162/231] Installing R-CRAN-mgcv-0:1.9. 100% | 328.6 MiB/s |   4.6 MiB |  00m00s
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[164/231] Installing R-CRAN-StanHeaders 100% | 206.1 MiB/s |  10.1 MiB |  00m00s
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[203/231] Installing R-java-0:4.4.0-1.f 100% |   0.0   B/s | 124.0   B |  00m00s
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[206/231] Installing ttmkfdir-0:3.0.9-7 100% | 120.9 MiB/s | 123.8 KiB |  00m00s
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>>> Running post-install scriptlet: xorg-x11-fonts-Type1-0:7.5-38.fc40.noarch
>>> Stop post-install scriptlet: xorg-x11-fonts-Type1-0:7.5-38.fc40.noarch
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>>> Running post-install scriptlet: java-21-openjdk-1:21.0.3.0.9-1.fc41.x86_64
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>>> Running trigger-install scriptlet: redhat-rpm-config-0:290-1.fc41.noarch
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>>> Running post-transaction scriptlet: crypto-policies-scripts-0:20240521-1.git
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>>> Running trigger-install scriptlet: glibc-common-0:2.39.9000-18.fc41.x86_64
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Warning: skipped PGP checks for 72 package(s).
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<Packet4f> {
      |                                           ^
/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<Packet2d> {
      |                                           ^
/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<Packet4f,4>& 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<Packet2d,2>& 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<PACKET_REAL, PACKET_CPLX, false, false> {          \
      |                                                            ^
/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<PACKET_CPLX, PACKET_REAL, false, false> {          \
      |                                                            ^
/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<PACKET_REAL, PACKET_CPLX, false, false> {          \
      |                                                            ^
/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<PACKET_CPLX, PACKET_REAL, false, false> {          \
      |                                                            ^
/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<float, 4>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<float, 4, 1> >’
   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<Eigen::Quaternion<float> >’
  266 |     Alignment = internal::traits<Coefficients>::Alignment,
      |                                                 ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46:   required from here
   24 |     ResAlignment = traits<Quaternion<float> >::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<float>::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::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<Eigen::Matrix<float, 4, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<float, 4, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<float, 4, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<float, 4, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<float, 4, 1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50:   required from ‘class Eigen::QuaternionBase<Eigen::Quaternion<float> >’
   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<float>’
  273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
      |       ^~~~~~~~~~
/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<float>::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<double, 4>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 4, 1> >’
   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<Eigen::Quaternion<double> >’
  266 |     Alignment = internal::traits<Coefficients>::Alignment,
      |                                                 ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47:   required from here
   98 |     ResAlignment = traits<Quaternion<double> >::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 4, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 4, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 4, 1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50:   required from ‘class Eigen::QuaternionBase<Eigen::Quaternion<double> >’
   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<double>’
  273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
      |       ^~~~~~~~~~
/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<double>::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<Eigen::SparseMatrix<double, 0, int> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7:   required from ‘class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 0, int> >’
   36 | class SparseCompressedBase
      |       ^~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7:   required from ‘class Eigen::SparseMatrix<double, 0, int>’
   96 | class SparseMatrix
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25:   required from here
   61 |   typedef Triplet<double> 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<double>::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<Packet4f> {
      |                                           ^
/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<Packet2d> {
      |                                           ^
/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<Packet4f,4>& 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<Packet2d,2>& 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<PACKET_REAL, PACKET_CPLX, false, false> {          \
      |                                                            ^
/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<PACKET_CPLX, PACKET_REAL, false, false> {          \
      |                                                            ^
/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<PACKET_REAL, PACKET_CPLX, false, false> {          \
      |                                                            ^
/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<PACKET_CPLX, PACKET_REAL, false, false> {          \
      |                                                            ^
/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<float, 4>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<float, 4, 1> >’
   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<Eigen::Quaternion<float> >’
  266 |     Alignment = internal::traits<Coefficients>::Alignment,
      |                                                 ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46:   required from here
   24 |     ResAlignment = traits<Quaternion<float> >::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<float>::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<float>::type’ {aka ‘__m128’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::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<Eigen::Matrix<float, 4, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<float, 4, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<float, 4, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<float, 4, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<float, 4, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<float, 4, 1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50:   required from ‘class Eigen::QuaternionBase<Eigen::Quaternion<float> >’
   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<float>’
  273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
      |       ^~~~~~~~~~
/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<float>::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<double, 4>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 4, 1> >’
   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<Eigen::Quaternion<double> >’
  266 |     Alignment = internal::traits<Coefficients>::Alignment,
      |                                                 ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47:   required from here
   98 |     ResAlignment = traits<Quaternion<double> >::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 4, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 4, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 4, 1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50:   required from ‘class Eigen::QuaternionBase<Eigen::Quaternion<double> >’
   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<double>’
  273 | class Quaternion : public QuaternionBase<Quaternion<_Scalar,_Options> >
      |       ^~~~~~~~~~
/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<double>::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> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  361 |     explicit shared_count( std::auto_ptr<Y> & r ): pi_( new sp_counted_impl_p<Y>( 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<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:251:65: warning: ‘template<class> 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<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:508:31: warning: ‘template<class> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  508 |     explicit shared_ptr( std::auto_ptr<Y> & r ): px(r.get()), pn()
      |                               ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:521:22: warning: ‘template<class> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  521 |     shared_ptr( std::auto_ptr<Y> && r ): px(r.get()), pn()
      |                      ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:604:34: warning: ‘template<class> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  604 |     shared_ptr & operator=( std::auto_ptr<Y> & r )
      |                                  ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:613:34: warning: ‘template<class> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  613 |     shared_ptr & operator=( std::auto_ptr<Y> && r )
      |                                  ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function ‘boost::shared_ptr<T>& boost::shared_ptr<T>::operator=(std::auto_ptr<_Up>&&)’:
/usr/local/lib/R/library/BH/include/boost/smart_ptr/shared_ptr.hpp:615:38: warning: ‘template<class> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
  615 |         this_type( static_cast< std::auto_ptr<Y> && >( r ) ).swap( *this );
      |                                      ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> 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<Eigen::SparseMatrix<double, 0, int> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7:   required from ‘class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 0, int> >’
   36 | class SparseCompressedBase
      |       ^~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7:   required from ‘class Eigen::SparseMatrix<double, 0, int>’
   96 | class SparseMatrix
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25:   required from here
   61 |   typedef Triplet<double> 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<double>::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<double, -1>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, -1, -1> >’
   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<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >’
   19 |   template<typename _MatrixType, int _UpLo> struct traits<LDLT<_MatrixType, _UpLo> >
      |                                                    ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59:   required from ‘struct Eigen::EigenBase<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >’
   42 |   typedef typename internal::traits<Derived>::StorageKind StorageKind;
      |                                                           ^~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7:   required from ‘class Eigen::SolverBase<Eigen::LDLT<Eigen::Matrix<double, -1, -1> > >’
   68 | class SolverBase : public EigenBase<Derived>
      |       ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49:   required from ‘class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >’
   59 | template<typename _MatrixType, int _UpLo> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, -1, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, -1, -1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, -1, -1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42:   required from ‘class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >’
   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<double>::type’ {aka ‘__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<double, -1, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, -1, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, -1, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, -1, 1>’
  178 | class Matrix
      |       ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19:   required from ‘class Eigen::LDLT<Eigen::Matrix<double, -1, -1> >’
  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<double>::type’ {aka ‘__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::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -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<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_LE>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Matrix<double, -1, -1>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Matrix<double, -1, -1>, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47:   required from ‘class Eigen::VectorBlock<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1>’
   56 | template<typename VectorType, int Size> 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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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<double, 1, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, -1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, -1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 1, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 1, -1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 1, -1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 1, -1>’
  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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Matrix<double, 1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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<double, -1, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Array<double, -1, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Array<double, -1, 1> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Array<double, -1, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7:   required from ‘class Eigen::Array<double, -1, 1>’
   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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Matrix<double, -1, -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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7:   required from ‘class Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>’
   56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44:   required from ‘stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> [with auto:244 = Eigen::Matrix<double, -1, -1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]’
   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<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]’
   56 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> [with auto:244 = Eigen::Matrix<double, -1, -1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]’
   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<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]’
   56 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59:   required from ‘stan::math::apply_vector_unary<Eigen::Matrix<double, -1, -1>, void>::apply<stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> >(const Eigen::Matrix<double, -1, -1>&, const stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>&)::<lambda(const auto:7&)> [with auto:7 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >]’
   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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::Matrix<double, -1, -1>, void>::apply<stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)> >(const Eigen::Matrix<double, -1, -1>&, const stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>&)::<lambda(const auto:7&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_ceil_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1, 0, -1, -1> > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil<Eigen::Matrix<double, -1, -1> >(const Eigen::Matrix<double, -1, -1>&)::<lambda(const auto:244&)>; T2 = Eigen::Matrix<double, -1, -1>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>]’
   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<double, -1, -1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0; stan::require_not_var_matrix_t<Container>* <anonymous> = 0]’
   56 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7:   required from ‘class Eigen::PartialReduxExpr<Eigen::Matrix<double, -1, -1>, Eigen::internal::member_minCoeff<double, double>, 0>’
   56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr<MatrixType, MemberOp, Direction> >::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >’
   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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Matrix<double, -1, 1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<Eigen::Matrix<double, -1, 1> >’
   52 | template<typename MatrixType> 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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -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<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<Eigen::VectorXd>(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<double>::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<int>&, 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<std::vector<double> >&)’:
/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<bool>&, const int&, const double&, const std::vector<int>&, std::vector<double>&)’:
/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<bool>::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<bool>::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<std::vector<double> >&)’:
/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<Eigen::Map<const Eigen::Matrix<double, -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<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<double>::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<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<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_<Pred>::************
      |                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  200 |       assert_not_arg( void (*)(Pred), typename assert_arg_pred_not<Pred>::type )
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  201 |     );
      |     ~                
/usr/local/lib/R/library/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses
  199 | failed ************ (boost::mpl::not_<Pred>::************
      |                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                     -
  200 |       assert_not_arg( void (*)(Pred), typename assert_arg_pred_not<Pred>::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<class _Category, class _Tp, class _Distance, class _Pointer, class _Reference> struct std::iterator’ is deprecated [-Wdeprecated-declarations]
  111 |         public std::iterator<IC, T> {
      |                     ^~~~~~~~
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<class _Category, class _Tp, class _Distance, class _Pointer, class _Reference> struct std::iterator’ is deprecated [-Wdeprecated-declarations]
  149 |         public std::iterator<IC, T> {
      |                     ^~~~~~~~
/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<class _Category, class _Tp, class _Distance, class _Pointer, class _Reference> struct std::iterator’ is deprecated [-Wdeprecated-declarations]
  204 |         public std::iterator<IC, T> {
      |                     ^~~~~~~~
/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> class std::auto_ptr’ is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations]
   48 | template<class T> T * get_pointer(std::auto_ptr<T> const& p)
      |                                        ^~~~~~~~
/usr/include/c++/14/bits/unique_ptr.h:59:28: note: declared here
   59 |   template<typename> class auto_ptr;
      |                            ^~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39:   required from ‘stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]’
   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<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   83 |   return apply_vector_unary<T>::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]’
   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<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   83 |   return apply_vector_unary<T>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]’
   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<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   83 |   return apply_vector_unary<T>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]’
   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<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   83 |   return apply_vector_unary<T>::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<double>::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<T_y, T_F, T_G, T_V, T_W, T_m0, T_C0> 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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 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::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2> >’
   48 | template<typename Derived> 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<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 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::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 0>, 2, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 5>, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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<const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, -1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >’
   52 | template<typename MatrixType> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::Matrix<double, -1, 1> >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Matrix<double, -1, -1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<Eigen::Matrix<double, -1, -1> >’
   52 | template<typename MatrixType> 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<Eigen::Lower>() * 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<double>::type’ {aka ‘__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<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -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<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<const Eigen::Matrix<double, -1, -1>, 1>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<Eigen::Lower>() * 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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<double>::type’ {aka ‘__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<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >’
   52 | template<typename MatrixType> 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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::LDLT<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1> >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >’
   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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_sqrt_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1>, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:0:   recursively required by substitution of ‘template<int Side, class Other> const Eigen::internal::triangular_solve_retval<Side, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Other> Eigen::TriangularViewImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase<U>&) const [with int Side = <missing>; Other = <missing>]’
  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<double>::type’ {aka ‘__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<double, -1, -1, 1, -1, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   32 |   enum { has_direct_access = (traits<Derived>::Flags & DirectAccessBit) ? 1 : 0,
      |                                                ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > >, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >’
   52 | template<typename MatrixType> 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<double>::type’ {aka ‘__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<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2> >’
   48 | template<typename Derived> 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<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 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<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 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<double>::type’ {aka ‘__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<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 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::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >’
   48 | template<typename Derived> 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<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 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::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::Transpose<Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> > >, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Transpose<const Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 6>, Eigen::Matrix<double, -1, -1> > > > >, 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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -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<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -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<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, void>’
   72 |       apply_scalar_unary<F, T>::apply(std::declval<T>()))>;
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
/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<Eigen::internal::scalar_sum_op<int, int>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t<Container>* <anonymous> = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t<Container>* <anonymous> = 0]’
  120 |   return apply_scalar_unary<lgamma_fun, T>::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<double>::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<std::complex<double> > 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<double>::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<int>::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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Matrix<double, -1, -1>, -1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Matrix<double, -1, -1>, -1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<double>::type’ {aka ‘__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<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >’
   52 | template<typename MatrixType> 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<StrictlyUpper>();
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::type’ {aka ‘__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::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<double>::type’ {aka ‘__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::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:59:34:   required from ‘class Eigen::RefBase<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> > >’
   59 | template<typename Derived> class RefBase
      |                                  ^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Ref.h:281:76:   required from ‘class Eigen::Ref<Eigen::Matrix<double, -1, -1>, 0, Eigen::OuterStride<> >’
  281 | template<typename PlainObjectType, int Options, typename StrideType> class Ref
      |                                                                            ^~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42:   required from ‘class Eigen::LLT<Eigen::Ref<Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<Eigen::Matrix<double, -1, -1>, void>’
   13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0:   required from here
  144 |   L_A.template triangularView<Eigen::StrictlyUpper>().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<double>::type’ {aka ‘__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::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   52 | template<typename MatrixType> 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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 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<double>::type’ {aka ‘__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<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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_lower_tri_self_transpose.hpp:28:0:   required from ‘auto stan::math::multiply_lower_tri_self_transpose(const T&) [with T = var_value<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
/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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<double>::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<Eigen::SparseMatrix<double, 1> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7:   required from ‘class Eigen::SparseCompressedBase<Eigen::SparseMatrix<double, 1> >’
   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<class OtherDerived> static std::true_type stan::is_base_pointer_convertible<Eigen::EigenBase, Eigen::SparseMatrix<double, 1> >::f(const Eigen::EigenBase<Derived>*) [with OtherDerived = <missing>]’
   29 |     = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::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<Eigen::EigenBase, Eigen::SparseMatrix<double, 1> >’
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71:   required from ‘struct stan::is_eigen<Eigen::SparseMatrix<double, 1> >’
   21 |     : bool_constant<is_base_pointer_convertible<Eigen::EigenBase, T>::value> {};
      |                                                                       ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:301:0:   required by substitution of ‘template<class T> class stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix<double, 1>]’
  301 |     (is_eigen<T>::value || is_kernel_expression_and_not_scalar<T>::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<return_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<double>::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<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> > >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7:   required from ‘class Eigen::SparseCompressedBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 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<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >, 0>’
   50 | class SparseMapBase<Derived,ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7:   required from ‘class Eigen::SparseMapBase<Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >, 1>’
  148 | class SparseMapBase<Derived,WriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7:   required from ‘class Eigen::Map<Eigen::SparseMatrix<double, 1>, 0, Eigen::Stride<0, 0> >’
  222 | class Map<SparseMatrix<MatScalar,MatOptions,MatIndex>, 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<Eigen::SparseMatrix<double, 1>, void>’
  129 | class arena_matrix<MatrixType, require_eigen_sparse_base_t<MatrixType>>
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0:   required from ‘class stan::math::vari_value<Eigen::SparseMatrix<double, 1>, void>’
  814 |   using InnerIterator = typename arena_matrix<PlainObject>::InnerIterator;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:419:0:   required from ‘const auto& stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix<double, 1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::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<return_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<double>::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<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, -1>’
   63 | template<typename MatrixType, int _DiagIndex> class Diagonal
      |                                                     ^~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21:   required from ‘class Eigen::Tridiagonalization<Eigen::Matrix<double, -1, -1> >’
   97 |             >::type SubDiagonalReturnType;
      |                     ^~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62:   required from ‘class Eigen::SelfAdjointEigenSolver<Eigen::Matrix<double, -1, -1> >’
  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<eigval_return_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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::adj_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44:   required from ‘stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)> [with auto:170 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   65 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)> [with auto:170 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   65 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59:   required from ‘stan::math::apply_vector_unary<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, void>::apply<stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&, const stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)>&)::<lambda(const auto:7&)> [with auto:7 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>, void>::apply<stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&, const stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)>&)::<lambda(const auto:7&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0> > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> >(const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>&)::<lambda(const auto:170&)>; T2 = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<const Eigen::Matrix<double, -1, -1>, 0>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   65 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1, 1, -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<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, void>’
   13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
/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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<vector_d>(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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 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::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -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/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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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/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<double>::type’ {aka ‘__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<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   52 | template<typename MatrixType> 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<double>::type’ {aka ‘__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<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -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<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, -1> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0:   required from here
   67 |     Eigen::Map<matrix_vi>(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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<matrix_d>(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<double>::type’ {aka ‘__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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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/mdivide_left_tri.hpp:85:0:   required from here
   85 |     adjA = -adjB * Map<matrix_d>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<double>::type’ {aka ‘__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<Eigen::Array<double, -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<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<Eigen::Array<double, -1, 1>, void>’
   13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
/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<double>::type’ {aka ‘__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::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 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<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47:   required from ‘class Eigen::VectorBlock<Eigen::Map<Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1>’
   56 | template<typename VectorType, int Size> 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<double>::type’ {aka ‘__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::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Array<double, -1, 1>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Array<double, -1, 1>, -1, 1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47:   required from ‘class Eigen::VectorBlock<Eigen::Array<double, -1, 1>, -1>’
   56 | template<typename VectorType, int Size> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Block<Eigen::Array<double, -1, 1>, -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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47:   required from ‘class Eigen::VectorBlock<Eigen::Block<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>’
   56 | template<typename VectorType, int Size> 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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -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<Eigen::internal::scalar_sqrt_op<double>, const Eigen::Block<Eigen::Array<double, -1, 1>, -1, 1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Matrix<int, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   42 |   typedef typename internal::traits<Derived>::StorageKind StorageKind;
      |                                                           ^~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7:   required from ‘class Eigen::DiagonalBase<Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   18 | class DiagonalBase : public EigenBase<Derived>
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7:   required from ‘class Eigen::DiagonalWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<vector_d>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::vari_value<double>*, -1, 1> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<vector_d>(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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<const Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0:   required from here
   27 |   Eigen::Map<vector_d>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0:   required from here
   27 |   Eigen::Map<vector_d>(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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1>, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, Eigen::Matrix<stan::math::var_value<double>, -1, 1> >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)> [with auto:12 = const Eigen::Matrix<stan::math::var_value<double>, -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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>; Args = {const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<var_value<double>, -1, 1>&; stan::require_eigen_dense_base_t<EigMat>* <anonymous> = 0; stan::require_not_st_arithmetic<T>* <anonymous> = 0]’
   73 |   return make_holder(
      |          ~~~~~~~~~~~^
   74 |       [](auto& a) {
      |       ~~~~~~~~~~~~~  
   75 |         return a.unaryExpr([](const auto& scal) { return value_of(scal); });
      |         ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   76 |       },
      |       ~~             
   77 |       std::forward<EigMat>(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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<double>::type’ {aka ‘__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::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1>, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Matrix<double, -1, -1> >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::VectorXd>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   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<double>::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<std::complex<double> > 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<double>::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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sqrt_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, -1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::Matrix<double, -1, 1> >’
   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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Diagonal<const Eigen::Matrix<double, -1, -1>, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<double>::type’ {aka ‘__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<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >’
   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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 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<double>::type’ {aka ‘__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<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7:   required from ‘class Eigen::internal::dense_product_base<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, 6>’
  126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7:   required from ‘class Eigen::ProductImpl<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<double>::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<double, 1>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >’
  179 |     typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
      |                                                                                 ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7:   required from ‘class Eigen::internal::dense_product_base<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, 6>’
  126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7:   required from ‘class Eigen::ProductImpl<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:86:7:   required from ‘class Eigen::SolveImpl<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1>, Eigen::Dense>’
   86 | class SolveImpl<Decomposition,RhsType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Solve.h:62:7:   required from ‘class Eigen::Solve<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, Eigen::Matrix<double, -1, 1> >’
   62 | class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<RhsType>::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<double>::type’ {aka ‘__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<const Eigen::Matrix<double, -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<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<const Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<T>&, int, int) [with T = double]’
  133 |   return Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>(
      |                 ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> > > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1>, 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<class OtherDerived> typename Eigen::ScalarBinaryOpTraits<double, typename Eigen::internal::traits<T>::Scalar, Eigen::internal::scalar_product_op<double, typename Eigen::internal::traits<T>::Scalar> >::ReturnType Eigen::MatrixBase<Eigen::Matrix<double, -1, 1> >::dot(const Eigen::MatrixBase<Derived>&) const [with OtherDerived = <missing>]’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > >’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> > > >’
   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<double>::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<std::complex<double> > 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<double>::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<int>::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<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::Matrix<double, -1, -1>, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0:   required from here
   72 |     Eigen::Map<Eigen::VectorXd>(&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<double>::type’ {aka ‘__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<Eigen::Matrix<double, 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<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 1>’
  223 | template<typename Derived> class MapBase<Derived, WriteAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<Eigen::Matrix<double, 1, -1>, void>’
   13 | class arena_matrix<MatrixType, require_eigen_dense_base_t<MatrixType>>
/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<double>::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<M>::log_prob(std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >&, std::vector<int>&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; stan::math::var = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’ was hidden [-Woverloaded-virtual=]
  159 |   inline math::var log_prob(std::vector<math::var>& theta,
stanExports_gMAP.h:1642: note:   by ‘model_gMAP_namespace::model_gMAP::log_prob’
 1642 |   log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,
/usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:154: warning: ‘double stan::model::model_base_crtp<M>::log_prob(std::vector<double>&, std::vector<int>&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’ was hidden [-Woverloaded-virtual=]
  154 |   inline double log_prob(std::vector<double>& theta, std::vector<int>& theta_i,
stanExports_gMAP.h:1642: note:   by ‘model_gMAP_namespace::model_gMAP::log_prob’
 1642 |   log_prob(std::vector<T_>& params_r, std::vector<int>& 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<M>::log_prob(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; stan::math::var = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’ was hidden [-Woverloaded-virtual=]
   96 |   inline math::var log_prob(Eigen::Matrix<math::var, -1, 1>& theta,
stanExports_gMAP.h:1642: note:   by ‘model_gMAP_namespace::model_gMAP::log_prob’
 1642 |   log_prob(std::vector<T_>& params_r, std::vector<int>& params_i,
/usr/local/lib/R/library/StanHeaders/include/src/stan/model/model_base_crtp.hpp:91: warning: ‘double stan::model::model_base_crtp<M>::log_prob(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’ 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<T_>& params_r, std::vector<int>& params_i,
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   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<double, -1, 1>; Mat2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >’
   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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_eigen_t<T>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/exp.hpp:63:44:   required from ‘stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)> [with auto:216 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >]’
   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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   62 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)> [with auto:216 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >]’
   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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   62 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59:   required from ‘stan::math::apply_vector_unary<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >, void>::apply<stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)> >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&, const stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)>&)::<lambda(const auto:7&)> [with auto:7 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > > >]’
   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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >, void>::apply<stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)> >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&, const stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)>&)::<lambda(const auto:7&)>; Args = {Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1, 0, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1, 0, -1, 1> >, const Eigen::Matrix<double, -1, 1, 0, -1, 1> > > > > > >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::exp<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > > >(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(const auto:216&)>; T2 = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_t<stan::is_eigen_matrix_base<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >]’
   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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   62 |   return apply_vector_unary<Container>::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<double>::type’ {aka ‘__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::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)> [with auto:703 = Eigen::Matrix<double, -1, 1>]’
  158 |         return plain_type_t<EigVec>::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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>; Args = {Eigen::Matrix<double, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<double, -1, 1>&; stan::require_eigen_vector_t<C>* <anonymous> = 0]’
  156 |   return stan::math::make_holder(
  157 |       [name, &idx](auto& v_ref) {
  158 |         return plain_type_t<EigVec>::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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_eigen_vt<std::is_arithmetic, Mat1, Mat2>* <anonymous> = 0; stan::require_not_eigen_row_and_col_t<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >’
   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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>; Mat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<double>::type’ {aka ‘__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<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<double, 3>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 3, 1> >’
   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<Eigen::Array<double, 3, 1> >’
   17 | struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Array<double, 3, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7:   required from ‘class Eigen::Array<double, 3, 1>’
   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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, 3, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Array<double, 3, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Array<double, 3, 1> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Array<double, 3, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7:   required from ‘class Eigen::Array<double, 3, 1>’
   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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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<const Eigen::Array<double, -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<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const std::vector<double>&>(const std::vector<double>&)::<lambda(auto:15&)>; Args = {const std::vector<double, std::allocator<double> >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<double>&; stan::require_std_vector_t<T>* <anonymous> = 0; stan::require_not_std_vector_t<typename stan::value_type<T>::type>* <anonymous> = 0]’
   72 |   return make_holder([](auto& x) { return T_map(x.data(), x.size()); },
      |          ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   73 |                      std::forward<T>(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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > > >’
   38 |                    >::type Scalar;
      |                            ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 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<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >’
   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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Select.h:52:7:   required from ‘class Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >’
   52 | class Select : public internal::dense_xpr_base< Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >::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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 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<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >(const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >&)::<lambda(const auto:10&)> [with auto:10 = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs<Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >(const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >&)::<lambda(const auto:10&)>; T2 = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >; stan::require_t<stan::is_eigen_array<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >]’
   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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   66 |   return apply_vector_unary<Container>::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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 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<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > > >(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >&)::<lambda(const auto:170&)>; T2 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >; stan::require_t<stan::is_eigen_array<typename stan::plain_type<T2, void>::type> >* <anonymous> = 0; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >]’
   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<Eigen::internal::scalar_abs_op<double>, const Eigen::Select<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::Array<double, 3, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> > >, Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, 3, 1> >, Eigen::Array<double, 3, 1> > >; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   65 |   return apply_vector_unary<Container>::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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75:   required from ‘stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32:   required from ‘stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, void>’
   72 |       apply_scalar_unary<F, T>::apply(std::declval<T>()))>;
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~
/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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::linspaced_op<double>, Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >; stan::require_not_var_matrix_t<Container>* <anonymous> = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t<Container>* <anonymous> = 0]’
  120 |   return apply_scalar_unary<lgamma_fun, T>::apply(x);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29:   required from ‘stan::return_type_t<T> stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t<T>* <anonymous> = 0; stan::return_type_t<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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double>::type’ {aka ‘__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<double, -1, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, -1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Array<double, -1, -1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Array<double, -1, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::Array<double, -1, -1> >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Array<double, -1, -1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Array.h:45:7:   required from ‘class Eigen::Array<double, -1, -1>’
   45 | class Array
      |       ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67:   required from ‘Derived& Eigen::ArrayBase<Derived>::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >; Scalar = double]’
   27 |   internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
      |                                              ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67:   required from ‘Derived& Eigen::ArrayBase<Derived>::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper<Eigen::Matrix<double, -1, -1> >; Scalar = double]’
   27 |   internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>());
      |                                              ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:22:   required from ‘bool Eigen::DenseBase<Derived>::allFinite() const [with Derived = Eigen::Matrix<double, -1, -1>]’
  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<double>::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<long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long unsigned int> >&) [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<size_t> 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<std::vector<long unsigned int> >::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<long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long unsigned int> >&) [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<size_t> 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<std::vector<long unsigned int> >::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<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>::<lambda(auto:3)>, const Eigen::Map<const Eigen::Array<int, -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<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>::<lambda(auto:3)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>::<lambda(auto:3)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>::<lambda(auto:3)>, const Eigen::Map<const Eigen::Array<int, -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<stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>::<lambda(auto:3)>, const Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)> [with auto:2 = Eigen::Map<const Eigen::Array<int, -1, 1>, 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<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of_rec<Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> > >(Eigen::Map<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >&&)::<lambda(auto:2&)>; Args = {Eigen::Map<const Eigen::Array<int, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<const Eigen::Array<int, -1, 1>, 0, Eigen::Stride<0, 0> >; <template-parameter-1-2> = void; <template-parameter-1-3> = void]’
  108 |   return make_holder(
      |          ~~~~~~~~~~~^
  109 |       [](auto& m) {
      |       ~~~~~~~~~~~~~  
  110 |         return m.unaryExpr([](auto x) { return value_of_rec(x); });
      |         ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       },
      |       ~~             
  112 |       std::forward<T>(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<int>; T_low = int; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_not_std_vector_vt<stan::is_container_or_var_matrix, T_y>* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 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<double>::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<double>; VecI = std::vector<int>; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]’:
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<int>::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<double, -1, 1>; VecI = std::vector<int>; stan::require_vector_t<T_y>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]’:
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<int>::min();
/usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp: In instantiation of ‘SEXPREC* rstan::stan_fit<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’:
stanExports_gMAP.cc:30:0:   required from here
   30 |     .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::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<double, 2>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 2, 1> >’
   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<Eigen::Matrix<double, 2, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 2, 1>’
  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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]’
  181 |   Eigen::Matrix<double, 2, 1> 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 2, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 2, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 2, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 2, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 2, 1>’
  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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]’
  181 |   Eigen::Matrix<double, 2, 1> 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<double>::type’ {aka ‘__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<double, 1, 1, 0, 1, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, 1, 0, 1, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 1, 1, 0, 1, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 1, 1, 0, 1, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 1, 1, 0, 1, 1>’
  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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = double]’
  182 |   Eigen::Matrix<double, 1, 1> 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 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<Eigen::internal::scalar_abs_op<double>, const Eigen::Array<double, 3, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double, double, double>]’
  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<double, double, double, double>]’
  204 |       grad_tuple_ab = grad_2F1_impl_ab<calc_a1_euler, calc_a2_euler, calc_b1>(
      |                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -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<Eigen::internal::scalar_cast_op<double, double>, const Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<class NewType> typename Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> > >::CastXpr<NewType>::Type Eigen::DenseBase<Eigen::Map<const Eigen::Array<double, -1, 1>, 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<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]’
  102 |   result << A.template cast<T_return>(), 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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::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<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<Eigen::Matrix<double, -1, 1> >::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<Eigen::Matrix<double, -1, -1> >(const char*, const char*, const Eigen::Matrix<double, -1, -1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, -1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* <anonymous> = 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<double, -1, -1>]’
   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<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<Eigen::Matrix<double, -1, 1> >::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<Eigen::Matrix<double, -1, 1> >(const char*, const char*, const Eigen::Matrix<double, -1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<Eigen::Matrix<double, -1, 1> >::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<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28:   required from ‘bool Eigen::DenseBase<Derived>::hasNaN() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, -1>, const Eigen::Matrix<double, -1, -1> >]’
  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<Derived>::allFinite() const [with Derived = Eigen::Matrix<double, -1, -1>]’
  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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28:   required from ‘bool Eigen::DenseBase<Derived>::hasNaN() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >]’
  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<Derived>::allFinite() const [with Derived = Eigen::Matrix<double, -1, 1>]’
  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<double>::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<U, V>* <anonymous> = 0; Idxs = {}]’:
/usr/local/lib/R/library/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0:   required from ‘std::vector<long unsigned int> stan::io::array_var_context::validate_dims(const std::vector<std::__cxx11::basic_string<char> >&, T, const std::vector<std::vector<long unsigned int> >&) [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<size_t> 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<double, -1, -1>]’:
/usr/local/lib/R/library/rstan/include/rstan/stan_fit.hpp:1253:0:   required from ‘SEXPREC* rstan::stan_fit<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1253 |     ret = stan::services::standalone_generate(model_, draws,
 1254 |             Rcpp::as<unsigned int>(seed), interrupt, logger, *sample_writer_ptr);
stanExports_gMAP.cc:30:0:   required from here
   30 |     .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::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<std::__cxx11::basic_string<char> >::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<Model>::failed() [with Model = boost::algorithm::FinderConcept<boost::algorithm::detail::token_finderF<boost::algorithm::detail::is_any_ofF<char> >, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<FinderT, IteratorT>::constraints() [with FinderT = boost::algorithm::detail::token_finderF<boost::algorithm::detail::is_any_ofF<char> >; IteratorT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   40 |             void constraints()
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint<Model>::failed() [with Model = boost::algorithm::FinderConcept<boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>, __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> > >]’:
/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<char>; FinderT = detail::first_finderF<const char*, is_equal>; FormatterT = detail::const_formatF<boost::iterator_range<const char*> >]’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char>; 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<FinderT, IteratorT>::constraints() [with FinderT = boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>; IteratorT = __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> >]’
   40 |             void constraints()
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::constraint<Model>::failed() [with Model = boost::algorithm::FormatterConcept<boost::algorithm::detail::const_formatF<boost::iterator_range<const char*> >, boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>, __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> > >]’:
/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<char>; FinderT = detail::first_finderF<const char*, is_equal>; FormatterT = detail::const_formatF<boost::iterator_range<const char*> >]’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char>; 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<FormatterT, FinderT, IteratorT>::constraints() [with FormatterT = boost::algorithm::detail::const_formatF<boost::iterator_range<const char*> >; FinderT = boost::algorithm::detail::first_finderF<const char*, boost::algorithm::is_equal>; IteratorT = __gnu_cxx::__normal_iterator<const char*, std::__cxx11::basic_string<char> >]’
   65 |             void constraints()
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, 1>, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47:   required from ‘class Eigen::VectorBlock<Eigen::Matrix<double, -1, 1>, -1>’
   56 | template<typename VectorType, int Size> 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<double, -1, -1>; DiagType = Eigen::Matrix<double, -1, 1>; SubDiagType = Eigen::Matrix<double, -1, 1>; 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<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]’:
stanExports_gMAP.h:1633:0:   required from ‘void model_gMAP_namespace::model_gMAP::write_array(RNG&, std::vector<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]’
 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<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_exp_op<double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58:   required from ‘stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)> [with auto:304 = Eigen::Matrix<double, -1, 1>]’
   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<T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp>::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp<Eigen::Matrix<double, -1, 1> >(const Eigen::Matrix<double, -1, 1>&)::<lambda(const auto:304&)>; T = Eigen::Matrix<double, -1, 1>]’
   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<double, -1, 1>; stan::require_container_st<std::is_arithmetic, Container>* <anonymous> = 0]’
   83 |   return apply_vector_unary<T>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<double, double, false, false, 1, 0>’:
/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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
      |                                                                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12:   required from ‘static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<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:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  460 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  461 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  462 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  465 |   typedef QuadPacket<RhsPacket> 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<double>::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<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::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<double, double, false, false, 1, 1>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42:   required from ‘struct Eigen::internal::gebp_kernel<double, double, long int, Eigen::internal::blas_data_mapper<double, long int, 0, 0, 1>, 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
      |                                                                                                             ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12:   required from ‘static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<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:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  460 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  461 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  462 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  465 |   typedef QuadPacket<RhsPacket> 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<double>::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<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::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<double, double, false, false, 1, 2>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45:   required from ‘struct Eigen::internal::gebp_kernel<double, double, long int, Eigen::internal::blas_data_mapper<double, long int, 0, 0, 1>, 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
      |                                                                                                             ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12:   required from ‘static void Eigen::selfadjoint_product_selector<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<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:425:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:426:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:427:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  460 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  461 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  462 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
  465 |   typedef QuadPacket<RhsPacket> 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<double>::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<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::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<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived> Eigen::DenseBase<Derived>::operator<<(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix<double, -1, 1>]’
  159 |   return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10:   required from ‘Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]’
  102 |   result << A.template cast<T_return>(), 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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::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<Derived>&) [with Derived = Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix<double, -1, 1>; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:478:32:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::mean() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  478 |   return Scalar(derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>())) / 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, -1>’
   63 | template<typename MatrixType, int _DiagIndex> 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, -1>’
   56 | template<typename VectorType, int Size> class VectorBlock
      |                                               ^~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::Matrix<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1, 0, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> > >, Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >’
   80 |     : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
      |                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0:   required by substitution of ‘template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; Types = {Eigen::Matrix<double, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   31 |   using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> 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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   35 |     arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2.val()));
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   35 |     arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2.val()));
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> 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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   39 |           const auto ret_adj = ret.adj().coeffRef(i, j);
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   49 |     arena_t<ret_type> ret(arena_m1.val().cwiseProduct(arena_m2));
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   51 |       arena_m1.adj().array() += arena_m2.array() * ret.adj().array();
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   51 |       arena_m1.adj().array() += arena_m2.array() * ret.adj().array();
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   51 |       arena_m1.adj().array() += arena_m2.array() * ret.adj().array();
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<double, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<ret_type> ret(arena_m1.cwiseProduct(arena_m2.val()));
stanExports_gMAP.h:952:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   29 |     = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::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<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  148 |   using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
/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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  150 |   arena_t<ret_type> 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<double, -1, 1>; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:949:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
  145 |     arena_t<return_t> res = arena_A.val() * arena_B.val().array();
stanExports_gMAP.h:969:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
  163 |       arena_B.adj().array() += arena_A * res.adj().array();
stanExports_gMAP.h:969:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
  170 |     arena_t<return_t> res = arena_A.val() * arena_B.array();
stanExports_gMAP.h:969:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<var_value<double>, -1, 1>; stan::require_not_matrix_t<T1>* <anonymous> = 0; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
  172 |       arena_A.adj() += (res.adj().array() * arena_B.array()).sum();
stanExports_gMAP.h:969:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:966:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   29 |     = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::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<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  148 |   using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
/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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:966:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  150 |   arena_t<ret_type> 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<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:966:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> > >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >’
   80 |     : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
      |                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0:   required by substitution of ‘template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<var_value<double>, -1, 1>; Mat2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_any_rev_matrix_t<T1, T2>* <anonymous> = 0]’
   31 |   using ret_type = return_var_matrix_t<inner_ret_type, Mat1, Mat2>;
stanExports_gMAP.h:982:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   34 |     auto arena_A_val = to_arena(arena_A.val());
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -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/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<const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >’
   80 |     : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
      |                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0:   required by substitution of ‘template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   36 |     using return_t
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   43 |             arena_A.adj() += res.adj_op() * arena_B_val.transpose();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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:43:0:   required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   43 |             arena_A.adj() += res.adj_op() * arena_B_val.transpose();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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:47:0:   required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   47 |             arena_A.adj() += res_adj * arena_B_val.transpose();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0> >’
   48 | template<typename Derived> 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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 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::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   48 |             arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<stan::math::value_of<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&>(arena_matrix<Eigen::Matrix<var_value<double>, -1, -1>, void>&)::<lambda(auto:12&)> [with auto:12 = stan::math::arena_matrix<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   66 |         = return_var_matrix_t<decltype(value_of(arena_A).eval() * arena_B), T1,
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -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/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<const Eigen::Product<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >’
   80 |     : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
      |                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0:   required by substitution of ‘template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Map<Eigen::Matrix<double, -1, -1, 0, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   65 |     using return_t
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -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<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map<Eigen::Matrix<double, -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:68:0:   required from ‘auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<var_value<double>, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]’
  113 |   using op_ret_type = decltype(a.val() + b.val());
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> > > >, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> > >’
   80 |     : bool_constant<math::disjunction<is_var_matrix<Types>...>::value> {};
      |                                                                 ^~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0:   required by substitution of ‘template<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >::val_Op, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>, Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1> >}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<var_value<double>, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]’
  114 |   using ret_type = return_var_matrix_t<op_ret_type, VarMat1, VarMat2>;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; VarMat2 = Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<stan::math::var_value<double>, -1, 1>&>(Eigen::Matrix<stan::math::var_value<double>, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<var_value<double>, -1, 1> >; stan::require_all_rev_matrix_t<VarMat1, VarMat2>* <anonymous> = 0]’
  117 |   arena_t<ret_type> ret(arena_a.val() + arena_b.val());
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  131 |     arena_t<promote_scalar_t<var, Mat>> res = inv_c * arena_m.val();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  134 |       arena_c.adj() -= (inv_times_adj * res.val().array()).sum();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  143 |       arena_m.adj().array() += inv_c * res.adj_op().array();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  143 |       arena_m.adj().array() += inv_c * res.adj_op().array();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  149 |     arena_t<promote_scalar_t<var, Mat>> res = inv_c * value_of(m).array();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryOp<stan::math::value_of<const Eigen::Matrix<var_value<double>, -1, 1>&>(const Eigen::Matrix<var_value<double>, -1, 1>&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 0]’
  149 |     arena_t<promote_scalar_t<var, Mat>> res = inv_c * value_of(m).array();
stanExports_gMAP.h:1028:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<var_value<double>, -1, 1>; stan::require_matrix_t<Mat>* <anonymous> = 0; stan::require_stan_scalar_t<T>* <anonymous> = 0; stan::require_all_st_var_or_arithmetic<Scalar, Mat>* <anonymous> = 0; stan::require_any_st_var<Scalar, Mat>* <anonymous> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >&)::<lambda(auto:14&)> [with auto:14 = const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]’
   57 |   return make_holder([](auto& x) { return x.array(); }, std::forward<T>(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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:1156:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1156 |                              stan::math::add(log_offset, theta)));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:1156:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1156 |                              stan::math::add(log_offset, theta)));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<Eigen::EigenBase, const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   29 |     = decltype(f(std::declval<std::remove_reference_t<Derived> *>()))::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<class ReturnType, class ... Types> using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix<ReturnType, Types ...>::value), stan::math::var_value<typename stan::math::promote_scalar_type<double, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type>, typename stan::math::promote_scalar_type<stan::math::var_value<double>, typename std::decay<typename stan::plain_type<T>::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >::val_Op, const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >; Types = {Eigen::Matrix<stan::math::var_value<double, void>, -1, 1, 0, -1, 1>}]’
   23 |     is_any_var_matrix<ReturnType, Types...>::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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  148 |   using ret_type = return_var_matrix_t<op_ret_type, VarMat>;
/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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:1156:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1156 |                              stan::math::add(log_offset, theta)));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<Eigen::CwiseUnaryView<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  150 |   arena_t<ret_type> 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_st_arithmetic<T>* <anonymous> = 0; stan::require_rev_matrix_t<VarMat>* <anonymous> = 0]’
  169 |   return add(b, a);
stanExports_gMAP.h:1156:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1156 |                              stan::math::add(log_offset, theta)));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::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<Eigen::Matrix<double, 2, 1> >(const char*, const char*, const Eigen::Matrix<double, 2, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 2, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, 2, 1>]’
   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<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = 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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<Eigen::Matrix<double, 2, 1> >::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<Eigen::Matrix<double, 1, 1, 0, 1, 1> >(const char*, const char*, const Eigen::Matrix<double, 1, 1, 0, 1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, 1, 1, 0, 1, 1>]’
   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<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = 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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<Eigen::Matrix<double, 1, 1, 0, 1, 1> >::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<Eigen::Matrix<double, 2, 1> >(const char*, const char*, const Eigen::Matrix<double, 2, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 2, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, 2, 1>]’
   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<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = 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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<Eigen::Matrix<double, 2, 1> >::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<Eigen::Matrix<double, 1, 1, 0, 1, 1> >(const char*, const char*, const Eigen::Matrix<double, 1, 1, 0, 1, 1>&)::<lambda(double)>; T = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, 1, 1, 0, 1, 1>]’
   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<T_x, T_sigma, T_l> stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix<double, 2, 1>; Tb = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Tz = double; stan::require_all_eigen_st<std::is_arithmetic, Ta, Tb>* <anonymous> = 0; stan::require_arithmetic_t<Tz>* <anonymous> = 0; stan::return_type_t<T_x, T_sigma, T_l> = 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<Ta1, Ta1, Tb, Tz> 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<double>; stan::require_all_arithmetic_t<Ta1, Ta2, Tb, Tz>* <anonymous> = 0; stan::return_type_t<Ta1, Ta1, Tb, Tz> = 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<double, double, double, double>]’
  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<std::integral_constant<bool, __v> >* <anonymous> = 0]’
  306 |   return internal::grad_2F1_impl<true, true, true, true>(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<true>(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<Eigen::Matrix<double, 1, 1, 0, 1, 1> >::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<T>::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::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>, 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<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 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::pole_error<boost::math::policies::errno_on_error>, boost::math::policies::promote_float<false>, boost::math::policies::promote_double<false>, 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<T1, T2, T3, T4> boost::math::ibeta_inv(T1, T2, T3, T4*, const Policy&) [with T1 = double; T2 = double; T3 = double; T4 = double; Policy = policies::policy<policies::overflow_error<boost::math::policies::errno_on_error>, policies::pole_error<boost::math::policies::errno_on_error>, policies::promote_double<false>, 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<T1, T2, T3, T4> = double]’
  992 |    rx = detail::ibeta_inv_imp(
      |         ~~~~~~~~~~~~~~~~~~~~~^
  993 |          static_cast<value_type>(a),
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~
  994 |          static_cast<value_type>(b),
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~
  995 |          static_cast<value_type>(p),
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~
  996 |          static_cast<value_type>(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<RT1, RT2, A> boost::math::ibeta_inv(RT1, RT2, RT3, const Policy&) [with RT1 = double; RT2 = double; RT3 = double; Policy = policies::policy<policies::overflow_error<boost::math::policies::errno_on_error>, policies::pole_error<boost::math::policies::errno_on_error>, policies::promote_double<false>, 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<RT1, RT2, A> = double]’
 1023 |    return ibeta_inv(a, b, p, static_cast<result_type*>(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<Derived>&) [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, member_sum<double, double>, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15:   required from ‘PacketType Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]’
  251 |       PacketScalar packet_res0 = eval.template packet<alignment,PacketScalar>(alignedStart);
      |                                  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/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<double>::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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 2, -1, true> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 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<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1> >; Scalar = double]’
  251 |       PacketScalar packet_res0 = eval.template packet<alignment,PacketScalar>(alignedStart);
      |                                  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:418:56:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
      |                                                                                 ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72:   required from ‘const Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::Scalar Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Scalar = double; Eigen::Index = long int]’
  183 |     return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
      |                      ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34:   required from ‘static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/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<double>::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<Scalar, Index, DataMapper, nr, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long int, 0>; 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2459 |           PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
      |                                                              ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 1, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long int, 1>; 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<typename unpacket_traits<Packet>::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<HalfPacket>::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<QuarterPacket>::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<HalfPacket> 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<QuarterPacket> 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<LhsScalar, RhsScalar, Index, DataMapper, mr, nr, ConjugateLhs, ConjugateRhs>::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<double, long int, 0, 0, 1>; 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<typename unpacket_traits<SResPacket>::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<typename unpacket_traits<typename unpacket_traits<SResPacket>::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<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SResPacket>::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<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SLhsPacket>::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<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SRhsPacket>::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<SwappedTraits::LhsProgress>=8,typename unpacket_traits<SAccPacket>::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<double, 16>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 4, 4> >’
   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<Eigen::Matrix<double, 4, 4> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 4, 4>’
  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<LhsScalar, RhsScalar, Index, mr, nr, ConjLhs, ConjRhs, ResInnerStride, UpLo>::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<ResScalar,BlockSize,BlockSize,ColMajor> 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 4, 4> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 4, 4> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 4> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >’
   48 | template<typename Derived> 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::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  369 |     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
      |                                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  352 |       Block<MatrixType,Dynamic,1> 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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1> >’
   48 | template<typename Derived> 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::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::DiagonalWrapper<const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:126:7:   required from ‘class Eigen::internal::dense_product_base<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, 6>’
  126 | class dense_product_base<Lhs, Rhs, Option, InnerProduct>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:152:7:   required from ‘class Eigen::ProductImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0> >’
   48 | template<typename Derived> 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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<double, -1, 1>; T2 = double; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7:   required from ‘class Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
  140 | class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~~
/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<double, -1, 1>; T2 = double; stan::require_any_eigen_t<T1, T2>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >’
   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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix<double, -1, 1>; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0; stan::require_all_not_st_var<Mat1, Mat2>* <anonymous> = 0]’
   45 |   return m1 + m2;
      |          ~~~^~~~
stanExports_gMAP.h:1156:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1156 |                              stan::math::add(log_offset, theta)));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> > >’
   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<model_gMAP_namespace::model_gMAP, false>; Scalar = double; XType = Eigen::Matrix<double, -1, 1>]’
  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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Matrix<double, -1, 1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0:   required from ‘Scalar stan::optimization::BFGSUpdate_HInv<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_identity_op<double>, Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<Eigen::internal::scalar_opposite_op<double>, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Scalar, DimAtCompile>::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -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<stan::math::value_of<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)>::<lambda(const auto:13&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> > >(Eigen::ArrayWrapper<const Eigen::Matrix<var_value<double>, -1, 1> >&&)::<lambda(auto:12&)> [with auto:12 = Eigen::ArrayWrapper<const Eigen::Matrix<stan::math::var_value<double>, -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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   79 |       = to_ref_if<!is_constant_all<T_scale>::value>(y_scaled * y_scaled);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   94 |                                  >= 2>(inv_sigma * y_scaled);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >]’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  102 |           square_y_scaled / nu_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::Array<double, -1, 1>]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  104 |       log1p(square_y_scaled_over_nu));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  107 |   T_partials_return logp = -sum((half_nu + 0.5) * log1p_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  124 |         (nu_val + 1) * (y_val - mu_val)
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  127 |       partials<0>(ops_partials) = -deriv_y_mu;
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  143 |             * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  144 |                + rep_deriv / nu_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  147 |       partials<3>(ops_partials) = rep_deriv / sigma_val;
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Array<double, -1, 1> >(const Eigen::Array<double, -1, 1>&)::<lambda(const auto:221&)> [with auto:221 = Eigen::Array<double, -1, 1>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   76 |       = to_ref_if<!is_constant_all<T_y, T_scale, T_loc>::value>(inv(sigma_val));
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Array<double, -1, 1> >(const Eigen::Array<double, -1, 1>&)::<lambda(const auto:170&)> [with auto:170 = Eigen::Array<double, -1, 1>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >]’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  102 |           square_y_scaled / nu_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Array<double, -1, 1> >(const Eigen::Array<double, -1, 1>&)::<lambda(const auto:239&)> [with auto:239 = Eigen::Array<double, -1, 1>]’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  121 |     const auto& square_sigma = square(sigma_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  124 |         (nu_val + 1) * (y_val - mu_val)
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
  147 |       partials<3>(ops_partials) = rep_deriv / sigma_val;
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(const auto:221&)> [with auto:221 = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   76 |       = to_ref_if<!is_constant_all<T_y, T_scale, T_loc>::value>(inv(sigma_val));
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1066 |           lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   85 |     logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   85 |     logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(const auto:221&)> [with auto:221 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   93 |         inv(beta_val - alpha_val));
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   97 |         partials<2>(ops_partials) = -inv_beta_minus_alpha * math::size(y);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   97 |         partials<2>(ops_partials) = -inv_beta_minus_alpha * math::size(y);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  105 |         partials<1>(ops_partials) = inv_beta_minus_alpha * math::size(y);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   94 |     logp = -sum(lgamma(alpha_val)) * N / math::size(alpha);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  100 |     logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  102 |       partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  102 |       partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  102 |       partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  109 |     logp -= sum(beta_val * y_val) * N / max_size(beta, y);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  113 |     partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  113 |     partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  113 |     partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  116 |     partials<2>(ops_partials) = alpha_val / beta_val - y_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  116 |     partials<2>(ops_partials) = alpha_val / beta_val - y_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   92 |       partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   92 |       partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   67 |           square(inv_sigma));
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   81 |   logp -= sum(log1p(square(y_minus_mu * inv_sigma)));
      |                            ~~~~~~~~~~~^~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   81 |   logp -= sum(log1p(square(y_minus_mu * inv_sigma)));
      |                     ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   81 |   logp -= sum(log1p(square(y_minus_mu * inv_sigma)));
      |               ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |           ~~^~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |                            ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |           ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  100 |           partials<0>(ops_partials) = -mu_deriv;
      |                                       ^~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  110 |       partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared)
      |                                   ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T1, T2> stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]’
   92 |       partials<0>(ops_partials) = -forward_as<beta_val_array>(beta_val);
      |                                   ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1127:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1127 |           lp_accum__.add(stan::math::exponential_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T1, T2> stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T1, T2> = var_value<double>]’
  100 |     partials<1>(ops_partials) = inv(beta_val) - y_val;
      |                                 ~~~~~~~~~~~~~~^~~~~~~
stanExports_gMAP.h:1127:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1127 |           lp_accum__.add(stan::math::exponential_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:221&)> [with auto:221 = Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   76 |       = to_ref_if<!is_constant_all<T_y, T_scale, T_loc>::value>(inv(sigma_val));
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::Array<double, -1, 1>, void>::apply(const Eigen::Array<double, -1, 1>&)::<lambda(auto:4&&)>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::Array<double, -1, 1>]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   70 |       = to_ref_if<!is_constant_all<T_prob>::value>(inv_logit(alpha_val));
      |                                                    ~~~~~~~~~^~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::Array<double, -1, 1> >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   72 |       = to_ref_if<!is_constant_all<T_prob>::value>(inv_logit(-alpha_val));
      |                                                    ~~~~~~~~~^~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   77 |   T_partials_return logp = sum(n_val * log_inv_logit_alpha
      |                                ~~~~~~^~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   78 |                                + (N_val - n_val) * log_inv_logit_neg_alpha);
      |                                  ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -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<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -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<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 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<const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>&&)::<lambda(auto:60&, auto:61&, auto:62&)> [with auto:60 = stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>; auto:61 = const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >; auto:62 = const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   80 |     logp += sum(binomial_coefficient_log(N_val, n_val)) * maximum_size
      |                 ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
   56 |                      >::type PacketReturnType;
      |                              ^~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<stan::math::Holder<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<stan::math::Holder<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<stan::math::Holder<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7:   required from ‘class stan::math::Holder<Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> >’
  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<Is ...>, const std::tuple<Args* ...>&) [with T = Eigen::CwiseBinaryOp<stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >; long unsigned int ...Is = {0}; Args = {stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>}; std::index_sequence<Is ...> = std::integer_sequence<long unsigned int, 0>]’
  312 |   return holder(std::forward<T>(expr), std::get<Is>(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<Is ...>, Args&& ...) [with F = stan::math::apply_scalar_binary<const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)> >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>&&)::<lambda(auto:60&, auto:61&, auto:62&)>; long unsigned int ...Is = {0, 1, 2}; Args = {stan::math::binomial_coefficient_log<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(const auto:242&, const auto:243&)>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >&, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >&}; std::index_sequence<Is ...> = std::integer_sequence<long unsigned int, 0, 1, 2>]’
  330 |   return make_holder_impl_construct_object(
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
  331 |       func(*std::get<Is>(res)...),
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~         
  332 |       std::make_index_sequence<std::tuple_size<decltype(ptrs)>::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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   80 |     logp += sum(binomial_coefficient_log(N_val, n_val)) * maximum_size
      |                 ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::Array<double, -1, 1> >(const Eigen::Array<double, -1, 1>&)::<lambda(const auto:216&)> [with auto:216 = Eigen::Array<double, -1, 1>]’
   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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector<int>; T_log_rate = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   72 |       = to_ref_if<!is_constant_all<T_log_rate>::value>(exp(alpha_val));
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector<int>; T_log_rate = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   79 |     logp -= sum(lgamma(n_val + 1.0)) * N / math::size(n);
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::lgamma_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector<int>; T_log_rate = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   79 |     logp -= sum(lgamma(n_val + 1.0)) * N / math::size(n);
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Array<double, -1, 1> >’
   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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = true; T_n = std::vector<int>; T_log_rate = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   83 |     partials<0>(ops_partials) = n_val - exp_alpha;
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7:   required from ‘Eigen::MapBase<Derived, 1>::ScalarWithConstIfNotLvalue& Eigen::MapBase<Derived, 1>::coeffRef(Eigen::Index) [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long int]’
   15 |       EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Derived>&, Eigen::DenseBase<Derived>&, const Eigen::JacobiRotation<OtherScalar>&) [with VectorX = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]’
  475 |     EIGEN_PLAIN_ENUM_MIN(evaluator<VectorX>::Alignment, evaluator<VectorY>::Alignment),
      |                                              ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40:   required from ‘void Eigen::MatrixBase<Derived>::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation<OtherScalar>&) [with OtherScalar = double; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<double, -1, -1>; DiagType = Eigen::Matrix<double, -1, 1>; SubDiagType = Eigen::Matrix<double, -1, 1>; Eigen::Index = long int]’
  548 |     internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(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<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51:   required from ‘class Eigen::internal::visitor_evaluator<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >’
   79 |     CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
      |                                                   ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17:   required from ‘void Eigen::DenseBase<Derived>::visit(Visitor&) const [with Visitor = Eigen::internal::min_coeff_visitor<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<T>::Scalar Eigen::DenseBase<Derived>::minCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long int; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; typename Eigen::internal::traits<T>::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<T>::Scalar Eigen::DenseBase<Derived>::minCoeff(IndexType*) const [with IndexType = long int; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; typename Eigen::internal::traits<T>::Scalar = double]’
  496 |       return minCoeff<PropagateFast>(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<double, -1, -1>; DiagType = Eigen::Matrix<double, -1, 1>; SubDiagType = Eigen::Matrix<double, -1, 1>; 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<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]’
  269 |   return internal::lpNorm_selector<Derived, p>::run(*this);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]’
  269 |   return internal::lpNorm_selector<Derived, p>::run(*this);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
 1384 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
 1464 | struct unary_evaluator<ArrayWrapper<TArgType> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::ArrayWrapper<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
 1384 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
 1464 | struct unary_evaluator<ArrayWrapper<TArgType> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_cmp_op<double, double, Eigen::internal::cmp_EQ>, const Eigen::ArrayWrapper<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Array<double, -1, 1> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  102 |           square_y_scaled / nu_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  107 |   T_partials_return logp = -sum((half_nu + 0.5) * log1p_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  124 |         (nu_val + 1) * (y_val - mu_val)
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  127 |       partials<0>(ops_partials) = -deriv_y_mu;
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  143 |             * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  144 |                + rep_deriv / nu_val);
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  147 |       partials<3>(ops_partials) = rep_deriv / sigma_val;
stanExports_gMAP.h:1012:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1012 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&>(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(auto:14&)> [with auto:14 = const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >]’
   57 |   return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
      |                                           ~~~~~~~^~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41:   required by substitution of ‘template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&>(const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >&)::<lambda(auto:14&)>; Args = {const Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1, 0, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1, 0, -1, 1> > > >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   94 |                                  >= 2>(inv_sigma * y_scaled);
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  102 |           square_y_scaled / nu_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  107 |   T_partials_return logp = -sum((half_nu + 0.5) * log1p_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  124 |         (nu_val + 1) * (y_val - mu_val)
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  125 |         / ((1 + square_y_scaled_over_nu) * square_sigma * nu_val));
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  127 |       partials<0>(ops_partials) = -deriv_y_mu;
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  143 |             * (digamma_half_nu_plus_half - digamma_half_nu - log1p_val
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  144 |                + rep_deriv / nu_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, void>::apply(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T_y0, T_param, T_t0, T_ts> 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<double, -1, 1>; T_dof = double; T_loc = double; T_scale = Eigen::MatrixWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > > >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = double]’
  147 |       partials<3>(ops_partials) = rep_deriv / sigma_val;
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   94 |                                  >= 2>(inv_sigma * y_scaled);
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = int; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1066 |           lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  109 |     logp -= sum(beta_val * y_val) * N / max_size(beta, y);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  113 |     partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  113 |     partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  116 |     partials<2>(ops_partials) = alpha_val / beta_val - y_val;
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  102 |     logp -= sum(beta_val * inv_y) * N / max_size(y, beta);
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  105 |           = (beta_val * inv_y - alpha_val - 1) * inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  108 |       partials<2>(ops_partials) = alpha_val / beta_val - inv_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   87 |                     >= 2>(logy_m_mu * inv_sigma_sq);
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -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<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, int>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |           = (logy_m_mu_div_sigma * logy_m_mu - 1) * inv_sigma;
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::log1p_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_fun; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(const auto:239&)> [with auto:239 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |           ~~^~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |                            ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   97 |           2 * y_minus_mu / (sigma_squared + y_minus_mu_squared));
      |           ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<int>, const Eigen::Array<int, -1, 1> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  100 |           partials<0>(ops_partials) = -mu_deriv;
      |                                       ^~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  110 |       partials<2>(ops_partials) = (y_minus_mu_squared - sigma_squared)
      |                                   ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~
stanExports_gMAP.h:1118:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   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<T, L, U> stan::math::cauchy_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1118 |           lp_accum__.add(stan::math::cauchy_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T1, T2> stan::math::exponential_lpdf(const T_y&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T1, T2> = double]’
  100 |     partials<1>(ops_partials) = inv(beta_val) - y_val;
      |                                 ~~~~~~~~~~~~~~^~~~~~~
stanExports_gMAP.h:1127:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1127 |           lp_accum__.add(stan::math::exponential_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   94 |                                  >= 2>(inv_sigma * y_scaled);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -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<Eigen::internal::scalar_opposite_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   96 |       partials<0>(ops_partials) = -scaled_diff;
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   99 |       partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma;
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<F, T, typename std::enable_if<stan::is_eigen<typename std::decay<_Tp2>::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   62 |     return x.unaryExpr([](auto&& x) {
      |            ~~~~~~~~~~~^~~~~~~~~~~~~~~
   63 |       return apply_scalar_unary<F, std::decay_t<decltype(x)>>::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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseUnaryOp<apply_scalar_unary<inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >(const Eigen::CwiseUnaryOp<apply_scalar_unary<inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::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<Eigen::CwiseUnaryOp<apply_scalar_unary<inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >(const Eigen::CwiseUnaryOp<apply_scalar_unary<inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >&)::<lambda(const auto:170&)> [with auto:170 = Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >]’
   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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = double]’
   77 |   T_partials_return logp = sum(n_val * log_inv_logit_alpha
      |                                ~~~~~~^~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = double]’
   78 |                                + (N_val - n_val) * log_inv_logit_neg_alpha);
      |                                  ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<int, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, int>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = double]’
   92 |           sum_n * inv_logit_neg_alpha
      |           ~~~~~~^~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, void>::apply(const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >&)::<lambda(auto:4&&)>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_opposite_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::inv_logit_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = false; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7:   required from ‘class Eigen::ArrayWrapper<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> > >’
   42 | class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
      |       ^~~~~~~~~~~~
/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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:14&)> [with auto:14 = const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >]’
   57 |   return make_holder([](auto& x) { return x.array(); }, std::forward<T>(v));
      |                                           ~~~~~~~^~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41:   required by substitution of ‘template<class F, class ... Args, stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >&>(const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:14&)>; Args = {const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1, 0, -1, 1> >&}; stan::require_plain_type_t<decltype (declval<F>()((declval<Args&>)()...))>* <anonymous> = <missing>]’
  370 |               decltype(std::declval<F>()(std::declval<Args&>()...))>* = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -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<Eigen::internal::scalar_difference_op<int, double>, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> > >’
   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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = false; T_n = std::vector<int>; T_log_rate = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = double]’
   83 |     partials<0>(ops_partials) = n_val - exp_alpha;
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44:   required from ‘static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::Matrix<double, -1, 1>; bool NeedToTranspose = false; ResScalar = double]’
   37 |     return a.template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Matrix<double, -1, 1>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0:   required from ‘int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<T, typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type>::sum() const [with T = stan::math::var_value<double>; typename std::enable_if<stan::is_var<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value<double>; stan::math::var = stan::math::var_value<double>]’
  135 |   inline var sum() const { return stan::math::sum(buf_); }
stanExports_gMAP.h:1164:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1164 |     return lp_accum__.sum();
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 4, 4>; 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, UpLo, Version>::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&) [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<MatrixType, OtherType, UpLo, false>::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix<double, -1, -1>; OtherType = Eigen::Matrix<double, -1, -1, 1, -1, -1>; int UpLo = 2; typename MatrixType::Scalar = double]’
  109 |     internal::general_matrix_matrix_triangular_product<Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  110 |       Scalar, OtherIsRowMajor ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  111 |       Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::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<MatrixType, UpLo>& Eigen::SelfAdjointView<MatrixType, Mode>::rankUpdate(const Eigen::MatrixBase<OtherDerived>&, const Scalar&) [with DerivedU = Eigen::Matrix<double, -1, -1, 1, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; unsigned int UpLo = 2; Scalar = double]’
  126 |   selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::type = double]’
   33 |   return result.setZero().template selfadjointView<Eigen::Upper>().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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Matrix<double, -1, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >’
   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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  374 |     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  374 |     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  374 |     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  374 |     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   62 |   check_not_nan(function, "Random variable", y_val);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::Array<double, -1, 1> >::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<stan::math::var_value<double>, -1, 1> >; Matrix2 = stan::math::arena_matrix<Eigen::Matrix<double, -1, 1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0; stan::require_st_arithmetic<Op>* <anonymous> = 0; stan::math::var = stan::math::var_value<double>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  105 |   return ops_partials.build(logp);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::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<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   64 |   check_positive(function, "Scale parameter", sigma_val);
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::Array<double, -1, 1> >::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<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<T_y0, T_param, T_t0, T_ts> 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<var_value<double>, -1, 1>; T_dof = double; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_N, T_size1, T_size2>* <anonymous> = 0; stan::return_type_t<T_y0, T_param, T_t0, T_ts> = var_value<double>]’
   85 |   check_positive_finite(function, "Scale parameter", sigma_val);
stanExports_gMAP.h:1036:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1036 |             lp_accum__.add(stan::math::student_t_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::Array<double, -1, 1> >::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   63 |   check_finite(function, "Location parameter", mu_val);
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   64 |   check_positive(function, "Scale parameter", sigma_val);
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   72 |   check_positive_finite(function, "Shape parameter", alpha_val);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::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<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   46 |   check_nonnegative(function, "Random variable", y_val);
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::Array<double, -1, 1> >::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   62 |   check_not_nan(function, "Random variable", y_val);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Array<double, -1, 1> >(const char*, const char*, const Eigen::Array<double, -1, 1>&)::<lambda(double)>; T = Eigen::Array<double, -1, 1>; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<double, -1, 1>]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   63 |   check_finite(function, "Location parameter", mu_val);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::Array<double, -1, 1> >::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   64 |   check_positive(function, "Scale parameter", sigma_val);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >&)::<lambda(double)>; T = Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 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<T_prob> stan::math::binomial_logit_lpmf(const T_n&, const T_N&, const T_prob&) [with bool propto = true; T_n = std::vector<int>; T_N = std::vector<int>; T_prob = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T_prob> = var_value<double>]’
   60 |   check_nonnegative(function, "Population size parameter", N_val);
      |   ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
stanExports_gMAP.h:1149:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1149 |             lp_accum__.add(stan::math::binomial_logit_lpmf<propto__>(r, r_n,
 1150 |                              theta));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<Eigen::Map<const Eigen::Matrix<int, -1, 1>, 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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; typename Eigen::internal::traits<T>::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<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1:   required from ‘ResultType Eigen::internal::member_sum<ResultType, Scalar>::operator()(const XprType&) const [with XprType = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, 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<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::Scalar Eigen::internal::evaluator<Eigen::PartialReduxExpr<MatrixType, MemberOp, Direction> >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >; MemberOp = Eigen::internal::member_sum<double, double>; int Direction = 1; Scalar = double; Eigen::Index = long int]’
  183 |     return m_functor(m_arg.template subVector<DirectionType(Direction)>(index));
      |            ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:268:34:   required from ‘static Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; Func = Eigen::internal::scalar_max_op<double, double, 0>; Evaluator = Eigen::internal::redux_evaluator<Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op<double, double, 0>; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:448:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  448 |   return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar, NaNPropagation>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::maxCoeff() const [with Derived = Eigen::PartialReduxExpr<const Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Matrix<double, -1, -1> >, Eigen::internal::member_sum<double, double>, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  466 |       return maxCoeff<PropagateFast>();
      |              ~~~~~~~~~~~~~~~~~~~~~~~^~
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0> >’
   48 | template<typename Derived> 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<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’
  370 |   typedef typename nested_eval<Rhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Scalar = double]’
  478 |       return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >]’
  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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>’
  369 |   typedef typename nested_eval<Lhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Scalar = double]’
  485 |       return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >]’
  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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, 1>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::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::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41:   required from ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
 1043 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  564 |     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
      |                                             ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]’
  269 |   return internal::lpNorm_selector<Derived, p>::run(*this);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  564 |     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
      |                                             ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits<T>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]’
  269 |   return internal::lpNorm_selector<Derived, p>::run(*this);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 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::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
  564 |     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
      |                                             ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51:   required from ‘class Eigen::internal::visitor_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> > >’
   79 |     CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
      |                                                   ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17:   required from ‘void Eigen::DenseBase<Derived>::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Diagonal<Eigen::Matrix<double, -1, -1>, 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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’
  369 |   typedef typename nested_eval<Lhs,1>::type LhsNested;
      |                                             ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42:   required from ‘static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::sub_assign_op<Scalar, Scalar>, 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<Scalar, Scalar>&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Rhs = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>]’
  178 |     generic_product_impl<Lhs, Rhs>::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<Eigen::Matrix<double, -1, -1>, -1, 1, false>; Src = Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31:   required from ‘ExpressionType& Eigen::NoAlias<ExpressionType, StorageBase>::operator-=(const StorageBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>; ExpressionType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’
   59 |       call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   62 |   check_not_nan(function, "Random variable", y_val);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >(const char*, const char*, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(double)>; T = Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >; Indexings = {}; stan::require_eigen_t<T>* <anonymous> = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* <anonymous> = 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<const Eigen::Matrix<double, -1, 1> >]’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   46 |   check_nonnegative(function, "Random variable", y_val);
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >::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<Eigen::Block<const Eigen::Matrix<double, -1, -1>, 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<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Functor = assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Functor = Eigen::internal::assign_op<double, double>; 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>]’
  836 |   call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Assign.h:66:28:   required from ‘Derived& Eigen::MatrixBase<Derived>::operator=(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<double, -1, -1>]’
   72 |     Eigen::Map<Eigen::VectorXd>(&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<Model, RNG_t>::standalone_gqs(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1253 |     ret = stan::services::standalone_generate(model_, draws,
 1254 |             Rcpp::as<unsigned int>(seed), interrupt, logger, *sample_writer_ptr);
stanExports_gMAP.cc:30:0:   required from here
   30 |     .method("standalone_gqs", &rstan::stan_fit<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25:   required from ‘void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’
  332 |       Base::template _init1<T>(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<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, -1>; Src = Eigen::Product<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Func = add_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]’
  850 |   typename plain_matrix_type<Src>::type tmp(src);
      |                                         ^~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18:   required from ‘Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  177 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, 1> >; Func = generic_product_impl<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25:   required from ‘void Eigen::PlainObjectBase<Derived>::_init1(const Eigen::DenseBase<ElseDerived>&) [with T = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]’
  332 |       Base::template _init1<T>(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<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, -1>; Src = Eigen::Product<Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Func = add_assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]’
  850 |   typename plain_matrix_type<Src>::type tmp(src);
      |                                         ^~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18:   required from ‘Derived& Eigen::MatrixBase<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >, Eigen::Transpose<Eigen::Matrix<double, -1, 1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  177 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >’
   48 | template<typename Derived> 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<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<double, double, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38:   required from ‘struct Eigen::internal::general_matrix_vector_product<long int, double, Eigen::internal::const_blas_data_mapper<double, long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long int, 0>, 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<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]’
  346 |     general_matrix_vector_product
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~                                                                                                   
  347 |         <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]’
  385 |     internal::gemv_dense_selector<Side,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  386 |                             (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
      |                             ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  387 |                             bool(internal::blas_traits<MatrixType>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<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:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   59 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   60 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   61 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<double, double, 1>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42:   required from ‘struct Eigen::internal::general_matrix_vector_product<long int, double, Eigen::internal::const_blas_data_mapper<double, long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long int, 0>, 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<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]’
  346 |     general_matrix_vector_product
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~                                                                                                   
  347 |         <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]’
  385 |     internal::gemv_dense_selector<Side,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  386 |                             (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
      |                             ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  387 |                             bool(internal::blas_traits<MatrixType>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<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:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   59 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   60 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   61 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<double, double, 2>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45:   required from ‘struct Eigen::internal::general_matrix_vector_product<long int, double, Eigen::internal::const_blas_data_mapper<double, long int, 1>, 1, false, double, Eigen::internal::const_blas_data_mapper<double, long int, 0>, 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<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Dest = Eigen::Matrix<double, -1, 1>; typename Dest::Scalar = double]’
  346 |     general_matrix_vector_product
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~                                                                                                   
  347 |         <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 7>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Scalar = double]’
  385 |     internal::gemv_dense_selector<Side,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  386 |                             (int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
      |                             ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  387 |                             bool(internal::blas_traits<MatrixType>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<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:44:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:45:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<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:46:27: warning: ignoring attributes on template argument ‘Eigen::internal::packet_traits<double>::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<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: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<double>::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<double>::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<double>::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   59 |   typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   60 |   typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::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<double>::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<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::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<double>::half’ {aka ‘__m128d’} [-Wignored-attributes]
   61 |   typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::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<double>::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<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::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<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   52 | template<typename MatrixType> 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
   52 | template<typename MatrixType> 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::Matrix<double, -1, 1>, -1, -1, false>; SrcXprType = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Functor = assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; SrcXprType = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op<double, double>; 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<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Eigen::Matrix<double, -1, 1>, -1, -1, false>; Src = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >]’
  836 |   call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived> Eigen::DenseBase<Derived>::operator<<(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix<double, -1, 1>]’
  159 |   return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10:   required from ‘Eigen::Matrix<typename stan::return_type<T1, T2>::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map<const Eigen::Array<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t<stan::is_eigen_col_vector<T> >* <anonymous> = 0; stan::require_stan_scalar_t<V>* <anonymous> = 0; typename stan::return_type<T1, T2>::type = double]’
  102 |   result << A.template cast<T_return>(), 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<double>; Tb = std::vector<double>; Tz = double; T_return = double; ArrayAT = Eigen::Array<double, 3, 1>; ArrayBT = Eigen::Array<double, 3, 1>; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<double>; Tb = std::vector<double>; Tz = double; stan::require_all_vector_t<T_y, T_high>* <anonymous> = 0; stan::require_stan_scalar_t<T2>* <anonymous> = 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<Ta, Tb, Tz>* <anonymous> = 0]’
  148 |   return hypergeometric_3F2(std::vector<Ta>(a), std::vector<Tb>(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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
  564 |     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
      |                                             ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >’
   52 | template<typename MatrixType> 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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:221:28:   required from ‘static typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::internal::lpNorm_selector<Derived, 1>::run(const Eigen::MatrixBase<Derived>&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::lpNorm() const [with int p = 1; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::Scalar = double]’
  269 |   return internal::lpNorm_selector<Derived, p>::run(*this);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74:   required from ‘Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; Rhs = Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51:   required from ‘static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::Matrix<double, -1, 1>; bool NeedToTranspose = false; ResScalar = double]’
   37 |     return a.template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Matrix<double, -1, 1>; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0:   required from ‘int stan::optimization::BFGSMinimizer<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’
  370 |   typedef typename nested_eval<Rhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]’
  478 |       return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>’
  369 |   typedef typename nested_eval<Lhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]’
  485 |       return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Array<double, -1, 1>, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = int; T_scale = int; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   82 |   T_partials_return logp = -0.5 * sum(y_scaled_sq);
stanExports_gMAP.h:1007:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1007 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(xi_eta, 0, 1));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Array<double, -1, 1>; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::Array<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::Array<double, -1, 1>; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::Array<double, -1, 1>; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   82 |   T_partials_return logp = -0.5 * sum(y_scaled_sq);
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = var_value<double>; T_scale = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1019:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1019 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1053:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1053 |         lp_accum__.add(stan::math::normal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::uniform_lpdf(const T_y&, const T_low&, const T_high&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_low = Eigen::Matrix<double, -1, 1>; T_high = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   85 |     logp -= sum(log(beta_val - alpha_val)) * N / max_size(alpha, beta);
stanExports_gMAP.h:1082:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1082 |           lp_accum__.add(stan::math::uniform_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  100 |     logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
  109 |     logp -= sum(beta_val * y_val) * N / max_size(beta, y);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<var_value<double>, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; T_loc = Eigen::Matrix<var_value<double>, -1, 1>; T_scale = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = var_value<double>]’
   87 |     logp -= sum(log(sigma_val)) * N / math::size(sigma);
stanExports_gMAP.h:1144:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1144 |             lp_accum__.add(stan::math::normal_lpdf<propto__>(y, theta, y_se));
stanExports_gMAP.h:1644:0:   required from ‘T_ model_gMAP_namespace::model_gMAP::log_prob(std::vector<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >’
   52 | template<typename MatrixType> 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0> >’
   48 | template<typename Derived> 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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  369 |     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51:   required from ‘static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; U = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]’
   37 |     return a.template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_inv_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  109 |     logp -= sum(beta_val * y_val) * N / max_size(beta, y);
stanExports_gMAP.h:1091:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1091 |           lp_accum__.add(stan::math::gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
  102 |     logp -= sum(beta_val * inv_y) * N / max_size(y, beta);
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<scalar_square_op<double>, const Eigen::CwiseUnaryOp<scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::Array<double, -1, 1> >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_square_op<double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, <template-parameter-1-2> >::add(const S&) [with S = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Matrix<double, -1, 1> >; stan::require_matrix_t<S>* <anonymous> = 0; T = double; <template-parameter-1-2> = void]’
   53 |     buf_.push_back(stan::math::sum(m));
      |                    ~~~~~~~~~~~~~~~^~~
stanExports_gMAP.h:1134:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_exp_op<double>, const Eigen::Array<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp<Eigen::internal::scalar_exp_op<double>, const Eigen::Array<double, -1, 1> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T_prob> stan::math::poisson_log_lpmf(const T_n&, const T_log_rate&) [with bool propto = false; T_n = std::vector<int>; T_log_rate = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix<double, -1, 1> >; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_n, T_prob>* <anonymous> = 0; stan::return_type_t<T_prob> = double]’
   76 |     logp -= sum(exp_alpha) * N / math::size(alpha);
stanExports_gMAP.h:1155:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector<double>; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1155 |             lp_accum__.add(stan::math::poisson_log_lpmf<propto__>(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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<false, jacobian>(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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 3>::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix<double, -1, -1>; LhsT = Eigen::Matrix<double, -1, -1>; RhsT = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>; Scalar = double; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 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::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >’
   48 | template<typename Derived> 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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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<Derived>&) [with Derived = Eigen::CwiseUnaryOp<scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:46:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  369 |     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  374 |     matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Rhs = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> > >’
   52 | template<typename MatrixType> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >’
   52 | template<typename MatrixType> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp: In instantiation of ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/usr/local/lib/R/library/BH/include/boost/concept_check.hpp:167:5:   required from ‘struct boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  125 |         struct IncrementableIteratorConcept : CopyConstructible<Iterator>
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16:   required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >]’:
/usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5:   required from ‘struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]’:
/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<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<X, Y>::~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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:136:13:   required from ‘struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/usr/local/lib/R/library/BH/include/boost/concept_check.hpp:233:5:   required from ‘struct boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >]’:
/usr/local/lib/R/library/BH/include/boost/concept_check.hpp:208:5:   required from ‘struct boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]’:
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:152:13:   required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<X, Y>::~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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:158:13:   required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:278:9:   required from ‘struct boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Iterator>::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >]’:
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:284:9:   required from ‘struct boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >’
   45 |     typedef boost::integral_constant<bool, value> type;
      |                                                   ^~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:72:8:   required from ‘struct boost::concepts::requirement_<void (*)(boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >)>’
   72 | struct requirement_<void(*)(Model)>
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Model>::~usage_requirements() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   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<boost::concepts::failed************ Model::************>::failed() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/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<char*, std::__cxx11::basic_string<char> > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/range/iterator_range_core.hpp:644:32:   required from ‘bool boost::operator==(const iterator_range<IteratorT>&, const iterator_range<Iterator2T>&) [with Iterator1T = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >; Iterator2T = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
  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<IteratorT>::equal(const boost::algorithm::split_iterator<IteratorT>&) const [with IteratorT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
  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<char*, std::__cxx11::basic_string<char> > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; mpl_::true_ = mpl_::bool_<true>]’
  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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator==(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >&; Difference1 = long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >&; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<T>::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::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::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Functor = assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Functor = Eigen::internal::assign_op<double, double>; 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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >; Func = assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_quotient_op<double, double>, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> > >]’
  836 |   call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Scalar, Index, StorageOrder, UpLo, ConjugateLhs, ConjugateRhs, Version>::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<Lhs, LhsMode, false, Rhs, 0, true>::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Scalar = double]’
  227 |     internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::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<Lhs, Rhs, Eigen::SelfAdjointShape, Eigen::DenseShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’
  805 |     selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  369 |     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
   62 |   conj_helper<Packet,Packet,NumTraits<Scalar>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
   63 |   conj_helper<Packet,Packet,NumTraits<Scalar>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 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::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >’
   52 | template<typename MatrixType> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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<double, long int, Eigen::internal::const_blas_data_mapper<double, long int, 1>, 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride>::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&, Eigen::internal::GemmParallelInfo<Index>*) [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<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
      |                                                                           ^~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:230:14:   required from ‘void Eigen::internal::gemm_functor<Scalar, Index, Gemm, Lhs, Rhs, Dest, BlockingType>::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo<Index>*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product<long int, double, 0, false, double, 1, false, 0, 1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Dest = Eigen::Matrix<double, -1, -1>; 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<double, long int, general_matrix_matrix_product<long int, double, 0, false, double, 1, false, 0, 1>, Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2504 |   typedef typename unpacket_traits<Packet>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2505 |   typedef typename unpacket_traits<typename unpacket_traits<Packet>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2508 |          HalfPacketSize = unpacket_traits<HalfPacket>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2509 |                  QuarterPacketSize = unpacket_traits<QuarterPacket>::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<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0> >’
   48 | template<typename Derived> 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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0> >’
   48 | template<typename Derived> 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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<Model>::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::CopyConstructible<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   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<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  125 |         struct IncrementableIteratorConcept : CopyConstructible<Iterator>
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/range/concepts.hpp:147:16:   required from ‘struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<TT>::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   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<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >]’
   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<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag>]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::incrementable_traversal_tag> >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<X, Y>::~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<Model>::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   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<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Iterator>::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   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<Model>::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::EqualityComparable<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   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<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::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<char*, std::__cxx11::basic_string<char> > >’
  147 |         struct SinglePassIteratorConcept
      |                ^~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<TT>::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   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<Model>::~usage_requirements() [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >]’
   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<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag>]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >::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<boost::Convertible<boost::iterators::random_access_traversal_tag, boost::iterators::single_pass_traversal_tag> >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<X, Y>::~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<Model>::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   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<char*, std::__cxx11::basic_string<char> > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >::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<boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<Iterator>::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> >]’
   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<Model>::~usage_requirements() [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’:
/usr/local/lib/R/library/BH/include/boost/concept/detail/general.hpp:50:47:   required from ‘static void boost::concepts::requirement<boost::concepts::failed************ Model::************>::failed() [with Model = boost::concepts::usage_requirements<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >]’
   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<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >’
   92 |     &::boost::concepts::requirement_<ModelFnPtr>::failed>    \
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/BH/include/boost/concept/detail/has_constraints.hpp:32:62:   required by substitution of ‘template<class Model> boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints<Model, (& Model::constraints)>*) [with Model = boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > >]’
   32 |   inline yes has_constraints_(Model*, wrap_constraints<Model,&Model::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >::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<boost::SinglePassRangeConcept<const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > > > >’
   45 |     typedef boost::integral_constant<bool, value> 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<Derived1, Derived2, typename boost::mpl::apply2<boost::iterators::detail::always_bool2, Derived1, Derived2>::type>::type boost::iterators::operator!=(const iterator_facade<Derived1, V1, TC1, Reference1, Difference1>&, const iterator_facade<Derived2, V2, TC2, Reference2, Difference2>&) [with Derived1 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string<char>; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string<char>; Difference1 = long int; Derived2 = transform_iterator<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string<char>; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string<char>; Difference2 = long int; typename detail::enable_if_interoperable<Derived1, Derived2, typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type>::type = bool; typename boost::mpl::apply2<detail::always_bool2, Derived1, Derived2>::type = bool]’
  966 |       return_prefix iterator_core_access::base_op(                              \
      |                     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  967 |           *static_cast<Derived1 const*>(&lhs)                                   \
      |           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  968 |         , *static_cast<Derived2 const*>(&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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >]’
 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<boost::algorithm::detail::copy_iterator_rangeF<std::__cxx11::basic_string<char>, __gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >, boost::use_default, boost::use_default>; <template-parameter-2-2> = void; _Tp = std::__cxx11::basic_string<char>; _Alloc = std::allocator<std::__cxx11::basic_string<char> >; allocator_type = std::allocator<std::__cxx11::basic_string<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; FinderT = detail::token_finderF<detail::is_any_ofF<char> >]’
  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<std::__cxx11::basic_string<char> >; RangeT = std::__cxx11::basic_string<char>&; PredicateT = detail::is_any_ofF<char>]’
  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<T>::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator<char*, std::__cxx11::basic_string<char> > >]’
   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<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::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<Scalar, Index, StorageOrder, UpLo, ConjugateLhs, ConjugateRhs, Version>::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<Lhs, LhsMode, false, Rhs, 0, true>::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Scalar = double]’
  227 |     internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<ActualLhsTypeCleaned>::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<Lhs, Rhs, Eigen::SelfAdjointShape, Eigen::DenseShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]’
  805 |     selfadjoint_product_impl<typename Lhs::MatrixType,Lhs::Mode,false,Rhs,0,Rhs::IsVectorAtCompileTime>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>; Lhs = Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl<Eigen::SelfAdjointView<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1>, Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  369 |     hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView<Lower>()
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  500 |   return first_aligned<unpacket_traits<DefaultPacketType>::alignment>(array, size);
      |                                                            ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0> >’
   48 | template<typename Derived> 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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Derived>::applyHouseholderOnTheRight(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Map<Eigen::Matrix<double, 1, -1>, 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<Derived>::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Derived>::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 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<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Map<Eigen::Matrix<double, 1, -1>, 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, 1>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Matrix<double, -1, 1>; Lhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’
  332 |       Base::template _init1<T>(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<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]’
  850 |   typename plain_matrix_type<Src>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>]’
  836 |   call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’
  332 |       Base::template _init1<T>(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<evaluator_assume_aliasing<Src>::value, void*>::type) [with Dst = Eigen::Matrix<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Func = assign_op<double, double>; typename enable_if<evaluator_assume_aliasing<Src>::value, void*>::type = void*; typename evaluator_traits<SrcXprType>::Shape = Eigen::DenseShape]’
  850 |   typename plain_matrix_type<Src>::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<double, -1, 1>; Src = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>]’
  836 |   call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32:   required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 0>; Derived = Eigen::Matrix<double, -1, 1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<double>::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<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long int, 0>; 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<Index, LhsScalar, LhsStorageOrder, ConjugateLhs, RhsScalar, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride>::run(Index, Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, ResScalar, Eigen::internal::level3_blocking<LhsScalar, RhsScalar>&, Eigen::internal::GemmParallelInfo<Index>*) [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<Scalar, Index, Gemm, Lhs, Rhs, Dest, BlockingType>::operator()(Index, Index, Index, Index, Eigen::internal::GemmParallelInfo<Index>*) const [with Scalar = double; Index = long int; Gemm = Eigen::internal::general_matrix_matrix_product<long int, double, 0, false, double, 1, false, 0, 1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Dest = Eigen::Matrix<double, -1, -1>; 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<double, long int, general_matrix_matrix_product<long int, double, 0, false, double, 1, false, 0, 1>, Eigen::Matrix<double, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, Eigen::Matrix<double, -1, -1>, 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<typename unpacket_traits<Packet>::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<HalfPacket>::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<QuarterPacket>::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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7:   required from ‘class Eigen::CwiseUnaryOpImpl<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
   55 | class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>, internal::no_assignment_operator
      |       ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:98:40:   required from ‘typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real Eigen::MatrixBase<Derived>::squaredNorm() const [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits<typename Eigen::internal::traits<T>::Scalar>::Real = double; typename Eigen::internal::traits<T>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true>; Derived = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Scalar, Index, DataMapper, nr, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::const_blas_data_mapper<double, long int, 0>; 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<Scalar, Index, Mode, false, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]’
  438 |     internal::product_triangular_matrix_matrix<Scalar, Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  439 |       Mode, LhsIsTriangular,
      |       ~~~~~~~~~~~~~~~~~~~~~~
  440 |       (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  441 |       (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  442 |       (internal::traits<Dest          >::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<Lhs, Rhs, Eigen::DenseShape, Eigen::TriangularShape, ProductTag>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]’
  783 |     triangular_product_impl<Rhs::Mode,false,Lhs,Lhs::RowsAtCompileTime==1, typename Rhs::MatrixType, false>::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<Lhs, Rhs, Derived>::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Lhs, Rhs, Derived>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2459 |           PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
      |                                                              ^~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 6>, Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -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<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 2>, Eigen::Matrix<double, -1, -1>, 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -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<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1>, Eigen::Matrix<double, -1, -1>, 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -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<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::TriangularView<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 5>, Eigen::Matrix<double, -1, -1>, 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, 1>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<double, -1, -1>; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix<double, -1, 1>]’
  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<MatrixType, UpLo>::compute(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; int _UpLo = 1]’
  526 |   m_info = internal::ldlt_inplace<UpLo>::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<MatrixType, UpLo>::LDLT(const Eigen::EigenBase<OtherDerived>&) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>; 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<typename Eigen::DenseBase<Derived>::PlainObject> Eigen::MatrixBase<Derived>::ldlt() const [with Derived = Eigen::Matrix<double, -1, -1>; typename Eigen::DenseBase<Derived>::PlainObject = Eigen::Matrix<double, -1, -1>]’
  683 |   return LDLT<PlainObject>(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<double, -1, -1>; stan::require_matrix_t<T>* <anonymous> = 0]’
   45 |   Eigen::LDLT<Eigen::MatrixXd> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 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::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘struct Eigen::internal::gemm_pack_rhs<double, long int, Eigen::internal::const_blas_data_mapper<double, long int, 1>, 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<Scalar, Index, 2, Mode, Conjugate, TriStorageOrder, 0, OtherInnerStride>::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking<Scalar, Scalar>&) [with Scalar = double; Index = long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]’
  233 |     gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr, RhsStorageOrder,false,true> 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<Lhs, Rhs, Side, Mode, 0, -1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Side = 2; int Mode = 2]’
  100 |     triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  101 |                                (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor, Rhs::InnerStrideAtCompileTime>
      |                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<OtherDerived>&) const [with int Side = 2; OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; _MatrixType = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; unsigned int _Mode = 2]’
  181 |   internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::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<Scalar, 1>::blocked(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; Scalar = double; Eigen::Index = long int]’
  364 |       if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
      |                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68:   required from ‘static bool Eigen::internal::LLT_Traits<MatrixType, 1>::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>]’
  408 |   { return llt_inplace<typename MatrixType::Scalar, Lower>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2504 |   typedef typename unpacket_traits<Packet>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2505 |   typedef typename unpacket_traits<typename unpacket_traits<Packet>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2508 |          HalfPacketSize = unpacket_traits<HalfPacket>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 2509 |                  QuarterPacketSize = unpacket_traits<QuarterPacket>::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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 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<Derived>::setZero() [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 4, 4>, 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<double, -1, -1, 1, -1, -1>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<double, -1, -1, 1, -1, -1>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0> >’
   48 | template<typename Derived> 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<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >’
   48 | template<typename Derived> 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::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, Eigen::DenseShape, Eigen::DenseShape, 7>’
  369 |   typedef typename nested_eval<Lhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >; Scalar = double]’
  485 |       return internal::generic_product_impl<typename Lhs::ConstRowXpr,Rhs,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Lhs = Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Transpose<Eigen::Matrix<double, -1, -1> >]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  564 |     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
      |                                             ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseUnaryOp<Eigen::internal::scalar_abs2_op<double>, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits<T>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, Eigen::DenseShape, Eigen::DenseShape, 7>’
  369 |   typedef typename nested_eval<Lhs,1>::type LhsNested;
      |                                             ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42:   required from ‘static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::sub_assign_op<Scalar, Scalar>, 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<Scalar, Scalar>&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Lhs = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>]’
  178 |     generic_product_impl<Lhs, Rhs>::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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Src = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31:   required from ‘ExpressionType& Eigen::NoAlias<ExpressionType, StorageBase>::operator-=(const StorageBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, 0>; ExpressionType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; StorageBase = Eigen::MatrixBase]’
   59 |       call_assignment_no_alias(m_expression, other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of ‘void Eigen::internal::gemm_pack_lhs<Scalar, Index, DataMapper, Pack1, Pack2, Packet, 0, Conjugate, PanelMode>::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long int; DataMapper = Eigen::internal::blas_data_mapper<double, long int, 0, 0, 1>; 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<Scalar, Index, 2, Mode, Conjugate, TriStorageOrder, 0, OtherInnerStride>::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking<Scalar, Scalar>&) [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<Lhs, Rhs, Side, Mode, 0, -1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Side = 2; int Mode = 2]’
  100 |     triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  101 |                                (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor, Rhs::InnerStrideAtCompileTime>
      |                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<OtherDerived>&) const [with int Side = 2; OtherDerived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; _MatrixType = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; unsigned int _Mode = 2]’
  181 |   internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::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<Scalar, 1>::blocked(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>; Scalar = double; Eigen::Index = long int]’
  364 |       if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
      |                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68:   required from ‘static bool Eigen::internal::LLT_Traits<MatrixType, 1>::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix<double, -1, -1>]’
  408 |   { return llt_inplace<typename MatrixType::Scalar, Lower>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<typename unpacket_traits<Packet>::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<HalfPacket>::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<QuarterPacket>::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<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’
   52 | template<typename MatrixType> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   48 |             arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >’
   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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; 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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; 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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<double, 64>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57:   required from ‘struct Eigen::internal::traits<Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   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<Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
      |       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7:   required from ‘class Eigen::Matrix<double, 8, 8, 0, 8, 8>’
  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<Scalar, Index, Mode, true, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [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<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> 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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’
  438 |     internal::product_triangular_matrix_matrix<Scalar, Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  439 |       Mode, LhsIsTriangular,
      |       ~~~~~~~~~~~~~~~~~~~~~~
  440 |       (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  441 |       (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  442 |       (internal::traits<Dest          >::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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::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<double, 8>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >’
  179 |     typedef typename internal::find_best_packet<Scalar,SizeAtCompileTime>::type PacketScalar;
      |                                                                                 ^~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<Scalar, Index, Mode, true, LhsStorageOrder, ConjugateLhs, RhsStorageOrder, ConjugateRhs, 0, ResInnerStride, Version>::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking<Scalar, Scalar>&) [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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]’
  438 |     internal::product_triangular_matrix_matrix<Scalar, Index,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  439 |       Mode, LhsIsTriangular,
      |       ~~~~~~~~~~~~~~~~~~~~~~
  440 |       (internal::traits<ActualLhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  441 |       (internal::traits<ActualRhsTypeCleaned>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  442 |       (internal::traits<Dest          >::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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  190 |          bool Stop = Size==Dynamic || (Size%unpacket_traits<PacketType>::size)==0 || is_same<PacketType,typename unpacket_traits<PacketType>::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<double>::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  208 |   typedef typename find_best_packet_helper<Size,typename packet_traits<T>::type>::type type;
      |                                                                                        ^~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>’
  370 |   typedef typename nested_eval<Rhs,1>::type RhsNested;
      |                                             ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43:   required from ‘static void Eigen::internal::Assignment<DstXprType, Eigen::Product<Lhs, Rhs, Options>, Eigen::internal::assign_op<Scalar, Scalar>, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op<Scalar, Scalar>&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>]’
  148 |     generic_product_impl<Lhs, Rhs>::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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>; Func = assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31:   required from ‘ExpressionType& Eigen::NoAlias<ExpressionType, StorageBase>::operator=(const StorageBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, 0>; ExpressionType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]’
   43 |       call_assignment_no_alias(m_expression, other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -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<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1> >’
   48 | template<typename Derived> 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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 1, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, -1, 1, -1, -1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>; 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<Derived>::setZero() [with Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >’
   48 | template<typename Derived> 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::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 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<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<double, 4, 4, 1, 4, 4>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 4, 4, 1, 4, 4> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, 4, 4, 1, 4, 4>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75:   required from ‘const Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; 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<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<double, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 1> >; Functor = Eigen::internal::assign_op<double, double>; 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<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  797 |       internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
      |       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19:   required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 0>; Derived = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Product<Eigen::Matrix<double, -1, -1, 1, -1, -1>, Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, 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<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<DstXprType, SrcXprType, Functor, Eigen::internal::Triangular2Dense>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op<double, double>]’
  856 |     call_triangular_assignment_loop<SrcXprType::Mode, (int(SrcXprType::Mode) & int(SelfAdjoint)) == 0>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::TriangularView<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >]’
  145 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   31 |     arena_L.adj() += ((res.adj().transpose() + res.adj())
   32 |                       * arena_L_val.template triangularView<Eigen::Lower>())
   33 |                          .template triangularView<Eigen::Lower>();
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:142:7:   required from ‘Eigen::DenseCoeffsBase<Derived, 0>::CoeffReturnType Eigen::DenseCoeffsBase<Derived, 0>::coeff(Eigen::Index) const [with Derived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long int]’
  142 |       EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
      |                                                         ^~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:182:19:   required from ‘Eigen::DenseCoeffsBase<Derived, 0>::CoeffReturnType Eigen::DenseCoeffsBase<Derived, 0>::operator()(Eigen::Index) const [with Derived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<double, -1, -1, 1, -1, -1>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; VectorsType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; CoeffsType = Eigen::VectorBlock<const Eigen::Matrix<double, -1, 1>, -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<VectorsType, CoeffsType, Side>::applyThisOnTheLeft(Dest&, Workspace&, bool) const [with Dest = Eigen::Matrix<double, -1, -1>; Workspace = Eigen::Matrix<double, -1, 1>; VectorsType = Eigen::Matrix<double, -1, -1>; CoeffsType = Eigen::Matrix<double, -1, 1>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Matrix<double, 1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Matrix<double, 1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Matrix<double, 1, -1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Matrix<double, 1, -1> >’
   52 | template<typename MatrixType> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Functor = div_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Functor = Eigen::internal::div_assign_op<double, double>; 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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Func = div_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp<scalar_constant_op<double>, Eigen::Matrix<double, -1, 1> >; Func = div_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator/=(const Scalar&) [with Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, false>; Scalar = double]’
   41 |   internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>());
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Map.h:94:79:   required from ‘class Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >’
   94 | template<typename PlainObjectType, int MapOptions, typename StrideType> 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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<LhsScalar, RhsScalar, Index, 1, Mode, Conjugate, 1>::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<const Matrix<RhsScalar,Dynamic,1> >(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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   44 |             arena_B.adj() += arena_A_val.transpose() * res.adj_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   48 | template<typename Derived> 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::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix<double, -1, 1>; 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 0, 8, 8> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 8, 8, 0, 8, 8>; 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<Derived>::setZero() [with Derived = Eigen::Matrix<double, 8, 8, 0, 8, 8>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 1, 0, 8, 1> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 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<Derived>::setZero() [with Derived = Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 0, 8, 8>, 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Functor = add_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op<double, double>; 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<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >]’
  177 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, -1, 1, false> >; typename Eigen::internal::traits<T>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
   52 | template<typename MatrixType> 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 4, 4, 1, 4, 4> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 4, 4, 1, 4, 4>; 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<Derived>::setZero() [with Derived = Eigen::Matrix<double, 4, 4, 1, 4, 4>]’
  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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41:   required from ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
 1043 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   48 |             arena_B.adj() += arena_A_val.transpose() * res_adj;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 1, 0, 8, 1>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 1, 0, 8, 1> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>& stan::math::arena_matrix<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
  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<MatrixType, typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t<T>* <anonymous> = 0; MatrixType = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::is_eigen_dense_base<typename std::decay<_Tp>::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>]’
   68 |     *this = other;
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0:   required from ‘stan::math::vari_value<T, typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<stan::math::conjunction<std::is_same<typename std::decay<_Tp>::type, typename stan::plain_type<T, void>::type>, stan::is_eigen_dense_base<T> >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix<double, -1, -1>; typename stan::plain_type<T>::type = Eigen::Matrix<double, -1, -1>]’
  722 |       : val_(x),
/usr/local/lib/R/library/StanHeaders/include/stan/math/rev/core/var.hpp:366:0:   required from ‘stan::math::var_value<T, typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product<Eigen::TriangularView<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t<T, S>* <anonymous> = 0; T = Eigen::Matrix<double, -1, -1>; typename std::enable_if<std::integral_constant<bool, ((stan::is_eigen<T>::value || stan::is_kernel_expression_and_not_scalar<T>::value) && std::is_floating_point<typename stan::value_type<T>::type>::value)>::value, void>::type = void; typename stan::value_type<T>::type = double]’
  366 |   var_value(S&& x) : vi_(new vari_type(std::forward<S>(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<Eigen::Matrix<double, -1, -1> >; stan::require_rev_matrix_t<T>* <anonymous> = 0]’
   27 |   arena_t<ret_type> res = arena_L_val.template triangularView<Eigen::Lower>()
/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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 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<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> > >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true> >’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41:   required from ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >’
 1043 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op<double, double>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Transpose<Eigen::Matrix<double, -1, -1> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >’
   52 | template<typename MatrixType> 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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Map<Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   38 |     arena_t<return_t> res = arena_A_val * arena_B_val;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   57 |     arena_t<return_t> res = arena_A * arena_B.val_op();
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> > >, -1, -1, true>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; Derived = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 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<T&&> stan::math::to_ref(T&&) [with T = const Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >&; stan::ref_type_t<T&&> = Eigen::Matrix<double, -1, -1, 1, -1, -1>]’
   18 |   return std::forward<T>(a);
      |                           ^
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29:   required from ‘Eigen::Matrix<typename stan::value_type<T>::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose<const Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0> >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; typename stan::value_type<T>::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::Matrix<double, -1, -1>, Eigen::TriangularView<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >, 2>, 0>; stan::require_eigen_t<T_desired>* <anonymous> = 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 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<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Map<Eigen::Matrix<double, 1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Rhs = Eigen::Matrix<double, -1, -1>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127:   required from ‘static void Eigen::internal::triangular_solve_vector<LhsScalar, RhsScalar, Index, 1, Mode, Conjugate, 1>::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<const Matrix<RhsScalar,Dynamic,1> >(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<Lhs, Rhs, Side, Mode, 0, 1>::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1> >; Rhs = Eigen::Matrix<double, -1, 1>; int Side = 1; int Mode = 2]’
   71 |     triangular_solve_vector<LhsScalar, RhsScalar, Index, Side, Mode, LhsProductTraits::NeedToConjugate,
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   72 |                             (int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor>
      |                             ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’
   52 | template<typename MatrixType> 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<Mode, false, Lhs, true, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator+=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, 1, false>]’
  177 |   call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0> >’
   48 | template<typename Derived> 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<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/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::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::Dense>’
  372 |   typedef typename plain_matrix_type_dense<T,typename traits<T>::XprKind, evaluator<T>::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<Eigen::Matrix<double, -1, -1>, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>’
  370 |   typedef typename nested_eval<Rhs,1>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>; Scalar = double]’
  478 |       return internal::generic_product_impl<Lhs,typename Rhs::ConstColXpr,DenseShape,DenseShape,GemvProduct>
      |              ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 8>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, -1, -1>; Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>]’
  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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0> >’
   48 | template<typename Derived> 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<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 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<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 0, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, Eigen::Matrix<double, -1, -1>, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits<T>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits<T>::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<double>&, 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<model_gMAP_namespace::model_gMAP, boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> > >; Model = model_gMAP_namespace::model_gMAP; RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -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<const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<double, -1, 1>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = add_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Matrix<double, -1, 1>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::CwiseUnaryOp<Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map<Eigen::Matrix<stan::math::var_value<double>, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >; T2 = Eigen::Matrix<var_value<double>, -1, 1>; stan::require_all_matrix_t<EigMat1, EigMat2>* <anonymous> = 0; stan::require_return_type_t<stan::is_var, T1, T2>* <anonymous> = 0; stan::require_not_row_and_col_vector_t<T1, T2>* <anonymous> = 0]’
   68 |     arena_t<return_t> res = arena_A.val_op() * arena_B;
stanExports_gMAP.h:997:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector<stan::math::var_value<double>, std::allocator<stan::math::var_value<double> > >; VecI = std::vector<int>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
  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<T_l>&, std::vector<int>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value<double>; std::ostream = std::basic_ostream<char>]’
 1644 |     return log_prob_impl<propto__, jacobian__>(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<double>&, std::vector<int>&, std::vector<double>&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_gMAP_namespace::model_gMAP; std::ostream = std::basic_ostream<char>]’
   40 |     var adLogProb = model.template log_prob<propto, jacobian_adjust_transform>(
   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<Model, RNG_t>::grad_log_prob(SEXP, SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; SEXP = SEXPREC*]’
 1183 |       lp = stan::model::log_prob_grad<true,true>(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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, 1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block<const Eigen::Matrix<double, -1, 1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<double, -1, 1>&; T2 = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<stan::model::rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >; stan::require_all_eigen_t<T_desired, T_actual>* <anonymous> = 0]’
   92 |   x = std::forward<T2>(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<double, -1, 1>&; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::Product<Eigen::Map<Eigen::Matrix<double, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Matrix<double, -1, 1>, 0>, const Eigen::CwiseNullaryOp<rvalue<Eigen::Matrix<double, -1, 1>&>(Eigen::Matrix<double, -1, 1>&, const char*, const index_multi&)::<lambda(auto:703&)>::<lambda(Eigen::Index)>, Eigen::Matrix<double, -1, 1> > >; stan::require_t<std::is_assignable<typename std::decay<_Tp>::type&, typename std::decay<_Tp2>::type> >* <anonymous> = 0; stan::require_all_not_t<internal::is_tuple<Tuple1>, internal::is_tuple<Tuple2> >* <anonymous> = 0]’
   60 |   internal::assign_impl(x, std::forward<U>(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<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = std::vector<double>; VecI = std::vector<int>; VecVar = std::vector<double>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]’
 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<double>&, std::vector<int>&, std::vector<double>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]’
 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<Model, RNG_t>::constrain_pars(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’
   48 | template<typename Derived> 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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> 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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Mode, 1>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >; Rhs = Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1> >’
   48 | template<typename Derived> 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<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 1, Eigen::Dense>’
  152 | class ProductImpl<Lhs,Rhs,Option,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Product.h:71:7:   required from ‘class Eigen::Product<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, -1>, 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 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<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Map<Eigen::Matrix<double, -1, 1>, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Map<Eigen::Matrix<double, -1, 1>, 0, Eigen::InnerStride<> >, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
   52 | template<typename MatrixType> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, 1, Version>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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<double, 8, 8, 1, 8, 8>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7:   required from ‘class Eigen::PlainObjectBase<Eigen::Matrix<double, 8, 8, 1, 8, 8> >’
   98 | class PlainObjectBase : public internal::dense_xpr_base<Derived>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53:   required from ‘class Eigen::Diagonal<Eigen::Matrix<double, 8, 8, 1, 8, 8>, 0>’
   63 | template<typename MatrixType, int _DiagIndex> 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block<const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>; U = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 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<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >’
   52 | template<typename MatrixType> 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Map<const Eigen::Matrix<double, -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<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7:   required from ‘class Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, Eigen::Matrix<double, 8, 8, 1, 8, 8> >’
   60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type, internal::no_assignment_operator
      |       ^~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30:   required from ‘Derived& Eigen::DenseBase<Derived>::setConstant(const Scalar&) [with Derived = Eigen::Matrix<double, 8, 8, 1, 8, 8>; 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<Derived>::setZero() [with Derived = Eigen::Matrix<double, 8, 8, 1, 8, 8>]’
  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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Matrix<double, -1, -1> >, -1, -1, false>; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, true>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix<double, -1, -1, 1, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:329:7:   required from ‘class Eigen::internal::BlockImpl_dense<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true, true>’
  329 | class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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<Mode, LhsIsTriangular, Lhs, false, Rhs, false>::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix<double, -1, -1>; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >; Rhs = Eigen::Matrix<double, -1, -1>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:357:7:   required from ‘class Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits<T>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 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::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false>, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Block<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose<const Eigen::Block<const Eigen::Map<const Eigen::Matrix<double, -1, 1>, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, 1, Version>::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<Mode, 1>::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]’
  327 |     internal::triangular_matrix_vector_product
      |     ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  328 |       <Index,Mode,
      |       ~~~~~~~~~~~~
  329 |        LhsScalar, LhsBlasTraits::NeedToConjugate,
      |        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  330 |        RhsScalar, RhsBlasTraits::NeedToConjugate,
      |        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  331 |        RowMajor>
      |        ~~~~~~~~~
  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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41:   required from ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
 1043 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 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<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, 1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<const Eigen::Block<const Eigen::Block<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block<Eigen::Transpose<Eigen::Block<Eigen::Block<Eigen::Matrix<double, -1, -1, 1, -1, -1>, 1, -1, true>, 1, -1, false> >, -1, 1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; SrcXprType = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op<double, double>; 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<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op<double, double>]’
  890 |   Assignment<ActualDstTypeCleaned,Src,Func>::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<Src>::value), void*>::type) [with Dst = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>; Src = Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op<double, double>; typename enable_if<(! evaluator_assume_aliasing<Src>::value), void*>::type = void*; typename evaluator_traits<SrcXprType>::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<Derived>::operator-=(const Eigen::MatrixBase<OtherDerived>&) [with OtherDerived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false>]’
  164 |   call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
      |   ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -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::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::Matrix<double, -1, -1>, 1, -1, false> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator<Eigen::Product<Lhs, Rhs, 1>, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix<double, -1, -1>; Rhs = Eigen::Matrix<double, -1, -1>; int ProductTag = 8; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Lhs = Eigen::Matrix<double, -1, -1>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, 1>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, 1>::Rhs = Eigen::Matrix<double, -1, -1>; 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<Scalar, DimAtCompile>::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix<double, -1, 1>]’
   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<FunctorType, QNUpdateType, Scalar, DimAtCompile>::step() [with FunctorType = stan::optimization::ModelAdaptor<model_gMAP_namespace::model_gMAP, false>; 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<long unsigned int>&, const std::vector<std::__cxx11::basic_string<char> >&, RNG_t&) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<Model, RNG_t>::call_sampler(SEXP) [with Model = model_gMAP_namespace::model_gMAP; RNG_t = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; 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<stan_model, boost::random::ecuyer1988> ::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<double>::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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -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::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1, 1, -1, -1>, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of ‘struct Eigen::internal::evaluator<Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -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::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
      |                                                                              ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8:   required from ‘struct Eigen::internal::evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> > >’
  722 | struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
      |        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >; Functor = sub_assign_op<double, double>]’
  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<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block<Eigen::Matrix<double, -1, -1>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, -1, -1> >, const Eigen::Block<const Eigen::Transpose<const Eigen::Matrix<double, -1, -1, 1, -1, -1> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op<double, double>; 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<OtherDerived>&) [with OtherDerived = Eigen::HouseholderSequence<Eigen::Matrix<double, -1, -1>, Eigen::Matrix<double, -1, 1>, 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<MatrixType, Size, IsComplex>::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; MatrixType = Eigen::Matrix<double, -1, -1>; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  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<double, -1, -1>; DiagonalType = Eigen::Matrix<double, -1, 1>; SubDiagonalType = Eigen::Matrix<double, -1, 1>; CoeffVectorType = Eigen::Matrix<double, -1, 1>]’
  434 |   tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, hcoeffs, extractQ);
      |   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39:   required from ‘Eigen::SelfAdjointEigenSolver<MatrixType>& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<OtherDerived>&, int) [with InputType = Eigen::Matrix<double, -1, -1>; _MatrixType = Eigen::Matrix<double, -1, -1>]’
  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<matrix_d> 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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::alignment,
      |                                                      ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -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<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7:   required from ‘class Eigen::CwiseUnaryViewImpl<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>’
  103 | class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7:   required from ‘class Eigen::CwiseUnaryView<Eigen::ArrayBase<Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map<Eigen::Array<stan::math::var_value<double>, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >’
   58 | class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::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<T, F>::chain() [with T = double; F = stan::math::sum<arena_allocator<var_value<double> > >(const std::vector<var_value<double>, arena_allocator<var_value<double> > >&)::<lambda(auto:446&)>]’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >’
   77 | class CwiseBinaryOp :
      |       ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:44:   required from ‘static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; bool NeedToTranspose = false; ResScalar = double]’
   37 |     return a.template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Model, BaseRNG>::T(stan::mcmc::diag_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::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<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; VecR = Eigen::Matrix<double, -1, 1>; VecI = std::vector<int>; VecVar = Eigen::Matrix<double, -1, 1>; stan::require_vector_like_vt<std::is_floating_point, VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::require_vector_vt<std::is_floating_point, VecVar>* <anonymous> = 0; std::ostream = std::basic_ostream<char>]’:
stanExports_gMAP.h:1616:0:   required from ‘void model_gMAP_namespace::model_gMAP::write_array(RNG&, Eigen::Matrix<double, -1, 1>&, Eigen::Matrix<double, -1, 1>&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; std::ostream = std::basic_ostream<char>]’
 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<M>::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<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’
  140 |     return static_cast<const M*>(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<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::CwiseUnaryOp<stan::math::apply_scalar_unary<stan::math::digamma_fun, Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, void>::apply(const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >&)::<lambda(auto:4&&)>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   92 |       partials<1>(ops_partials) = log_beta - digamma(alpha_val) - log_y;
stanExports_gMAP.h:1100:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix<double, -1, 1>; VecI = Eigen::Matrix<int, -1, 1>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_job_param, -1, 1>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1639 |     return log_prob_impl<propto__, jacobian__>(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<M>::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’
  115 |     return static_cast<const M*>(this)->template log_prob<true, false>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix<double, -1, 1>; VecI = Eigen::Matrix<int, -1, 1>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_job_param, -1, 1>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1639 |     return log_prob_impl<propto__, jacobian__>(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<M>::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’
  115 |     return static_cast<const M*>(this)->template log_prob<true, false>(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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34:   required from ‘class Eigen::ArrayBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >’
   39 | template<typename Derived> class ArrayBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -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<Eigen::internal::scalar_difference_op<double, double>, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > >’
   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<T, L, U> stan::math::lognormal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<double, -1, 1>; T_loc = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = double]’
   70 |   const auto& logy_m_mu = to_ref(log_y - mu_val);
stanExports_gMAP.h:1109:0:   required from ‘stan::scalar_type_t<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix<double, -1, 1>; VecI = Eigen::Matrix<int, -1, 1>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1109 |           lp_accum__.add(stan::math::lognormal_lpdf<propto__>(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<T_job_param, -1, 1>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1639 |     return log_prob_impl<propto__, jacobian__>(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<M>::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’
  115 |     return static_cast<const M*>(this)->template log_prob<true, false>(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<double>::type’ {aka ‘__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<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >’
   52 | template<typename MatrixType> 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -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<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >’
   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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:37:51:   required from ‘static Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::ResScalar Eigen::internal::dot_nocheck<T, U, NeedToTranspose>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Matrix<double, -1, 1>; U = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; bool NeedToTranspose = false; ResScalar = double]’
   37 |     return a.template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Matrix<double, -1, 1>, const Eigen::Matrix<double, -1, 1> >; Derived = Eigen::Matrix<double, -1, 1>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Model, BaseRNG>::T(stan::mcmc::diag_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::Transpose<const Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0> >, const Eigen::Matrix<double, -1, 1> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64:   required from ‘static void Eigen::internal::generic_product_impl<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15:   required from ‘stan::value_type_t<T> stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseBinaryOp<Eigen::internal::scalar_sum_op<double, double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> >, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Array<double, -1, 1> > >, const Eigen::CwiseUnaryOp<Eigen::internal::scalar_log_op<double>, const Eigen::ArrayWrapper<const Eigen::Matrix<double, -1, 1> > > >; stan::require_eigen_vt<std::is_arithmetic, T>* <anonymous> = 0; stan::value_type_t<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<T, L, U> stan::math::inv_gamma_lpdf(const T_y&, const T_shape&, const T_scale&) [with bool propto = true; T_y = Eigen::Matrix<double, -1, 1>; T_shape = Eigen::Matrix<double, -1, 1>; T_scale = Eigen::Matrix<double, -1, 1>; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t<T_y, T_scale_succ, T_scale_fail>* <anonymous> = 0; stan::return_type_t<T, L, U> = 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<T2> model_gMAP_namespace::model_gMAP::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; VecR = Eigen::Matrix<double, -1, 1>; VecI = Eigen::Matrix<int, -1, 1>; stan::require_vector_like_t<VecR>* <anonymous> = 0; stan::require_vector_like_vt<std::is_integral, VecI>* <anonymous> = 0; stan::scalar_type_t<T2> = double; std::ostream = std::basic_ostream<char>]’
 1100 |           lp_accum__.add(stan::math::inv_gamma_lpdf<propto__>(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<T_job_param, -1, 1>&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream<char>]’
 1639 |     return log_prob_impl<propto__, jacobian__>(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<M>::log_prob_propto(Eigen::VectorXd&, std::ostream*) const [with M = model_gMAP_namespace::model_gMAP; Eigen::VectorXd = Eigen::Matrix<double, -1, 1>; std::ostream = std::basic_ostream<char>]’
  115 |     return static_cast<const M*>(this)->template log_prob<true, false>(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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment),Derived>(m);
      |                                                                          ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of ‘class Eigen::DenseCoeffsBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >’
   48 | template<typename Derived> 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::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true, false>’
  172 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
      |                                                                                                       ^~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:154:7:   required from ‘class Eigen::BlockImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true, Eigen::Dense>’
  154 | class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Block.h:103:81:   required from ‘class Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>’
  103 | template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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<Eigen::Matrix<double, 1, -1> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<Eigen::Matrix<double, 1, -1> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<Eigen::Matrix<double, 1, -1>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > > >’
   52 | template<typename MatrixType> 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<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >; Rhs = Eigen::Matrix<double, -1, -1>; Dest = Eigen::Matrix<double, 1, -1>; 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >’
   52 | template<typename MatrixType> class Transpose
      |                                     ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:23:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7:   required from ‘class Eigen::CwiseBinaryOpImpl<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >, 2>’
  481 | class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > > >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > > >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37:   required from ‘class Eigen::TransposeImpl<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> >, Eigen::Dense>’
  118 | template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
      |                                     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37:   required from ‘class Eigen::Transpose<const Eigen::Transpose<const Eigen::Matrix<double, -1, 1> > >’
   52 | template<typename MatrixType> 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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__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::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 0>’:
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 1>’
  302 | class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7:   required from ‘class Eigen::DenseCoeffsBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 3>’
  555 | class DenseCoeffsBase<Derived, DirectWriteAccessors>
      |       ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34:   required from ‘class Eigen::DenseBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true> >’
   41 | template<typename Derived> class DenseBase
      |                                  ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34:   required from ‘class Eigen::MatrixBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true> >’
   48 | template<typename Derived> class MatrixBase
      |                                  ^~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34:   required from ‘class Eigen::MapBase<Eigen::Block<Eigen::Transpose<Eigen::Matrix<double, 1, -1> >, -1, 1, true>, 0>’
   37 | template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
      |                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 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::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41:   required from ‘struct Eigen::internal::unary_evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>’
  311 |     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
      |                                         ^~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8:   required from ‘struct Eigen::internal::evaluator<Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >’
   90 | struct evaluator : public unary_evaluator<T>
      |        ^~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8:   required from ‘struct Eigen::internal::evaluator<const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> > >’
  100 | struct evaluator<const T>
      |        ^~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41:   required from ‘struct Eigen::internal::binary_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>’
  739 |     CoeffReadCost = int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
 1071 |     PacketAlignment = unpacket_traits<PacketScalar>::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<Derived>&) [with Derived = Eigen::CwiseBinaryOp<scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<Func, Evaluator, 3, 0>::Scalar Eigen::internal::redux_impl<Func, Evaluator, 3, 0>::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op<double, double>; Evaluator = Eigen::internal::redux_evaluator<Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -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<T>::Scalar Eigen::DenseBase<Derived>::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op<double, double>; Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  418 |   return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func, derived());
      |          ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Redux.h:463:25:   required from ‘typename Eigen::internal::traits<T>::Scalar Eigen::DenseBase<Derived>::sum() const [with Derived = Eigen::CwiseBinaryOp<Eigen::internal::scalar_conj_product_op<double, double>, const Eigen::Transpose<const Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true> >, const Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true> >; typename Eigen::internal::traits<T>::Scalar = double]’
  463 |   return derived().redux(Eigen::internal::scalar_sum_op<Scalar,Scalar>());
      |          ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:50:63:   required from ‘static Eigen::internal::dot_nocheck<T, U, true>::ResScalar Eigen::internal::dot_nocheck<T, U, true>::run(const Eigen::MatrixBase<Derived>&, const Eigen::MatrixBase<U>&) [with T = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; U = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; ResScalar = double]’
   50 |     return a.transpose().template binaryExpr<conj_prod>(b).sum();
      |            ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~
/usr/local/lib/R/library/RcppEigen/include/Eigen/src/Core/Dot.h:84:58:   required from ‘typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType Eigen::MatrixBase<Derived>::dot(const Eigen::MatrixBase<OtherDerived>&) const [with OtherDerived = Eigen::Block<const Eigen::Matrix<double, -1, -1>, -1, 1, true>; Derived = Eigen::Block<const Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits<typename Eigen::internal::traits<T>::Scalar, typename Eigen::internal::traits<OtherDerived>::Scalar>::ReturnType = double; typename Eigen::internal::traits<T>::Scalar = double; typename Eigen::internal::traits<OtherDerived>::Scalar = double]’
   84 |   return internal::dot_nocheck<Derived,OtherDerived>::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<Lhs, Rhs, Eigen::DenseShape, Eigen::DenseShape, 6>::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix<double, 1, 1, 0, 1, 1>; Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>]’
  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<Eigen::Product<Lhs, Rhs, Option>, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Lhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; typename Eigen::internal::traits<typename Eigen::Product<Lhs, Rhs, Option>::Rhs>::Scalar = double; typename Eigen::Product<Lhs, Rhs, Option>::Rhs = Eigen::Matrix<double, -1, 1>; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 0>]’
  124 |     generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::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<Eigen::Product<Lhs, Rhs, Option> >::evaluator(const XprType&) [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Options = 0; XprType = Eigen::Product<Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>, Eigen::Matrix<double, -1, 1>, 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<Lhs, Rhs, Option, 6>::operator const Scalar() const [with Lhs = Eigen::Product<Eigen::CwiseBinaryOp<Eigen::internal::scalar_product_op<double, double>, const Eigen::CwiseNullaryOp<Eigen::internal::scalar_constant_op<double>, const Eigen::Matrix<double, 1, -1> >, const Eigen::Transpose<Eigen::Matrix<double, -1, 1> > >, Eigen::Matrix<double, -1, -1>, 0>; Rhs = Eigen::Matrix<double, -1, 1>; int Option = 0; Scalar = double]’
  137 |     return internal::evaluator<ProductXpr>(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<Model, BaseRNG>::T(stan::mcmc::dense_e_point&) [with Model = model_gMAP_namespace::model_gMAP; BaseRNG = boost::random::additive_combine_engine<boost::random::linear_congruential_engine<unsigned int, 40014, 0, 2147483563>, boost::random::linear_congruential_engine<unsigned int, 40692, 0, 2147483399> >]’
   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<double>::type’ {aka ‘__m128d’} [-Wignored-attributes]
  654 |   return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::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