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tmbstan: MCMC Sampling from 'TMB' Model Object using 'Stan'

Enables all 'rstan' functionality for a 'TMB' model object, in particular MCMC sampling and chain visualization. Sampling can be performed with or without Laplace approximation for the random effects. This is demonstrated in Monnahan & Kristensen (2018) <doi:10.1371/journal.pone.0197954>.

Version: 1.0.91
Depends: rstan
Imports: methods, Rcpp, TMB
LinkingTo: StanHeaders, rstan, BH, Rcpp, RcppEigen, TMB, RcppParallel
Published: 2023-08-26
DOI: 10.32614/CRAN.package.tmbstan
Author: Kasper Kristensen
Maintainer: Kasper Kristensen <kaskr at dtu.dk>
BugReports: https://github.com/kaskr/tmbstan/issues
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: tmbstan citation info
Materials: NEWS
In views: MixedModels
CRAN checks: tmbstan results

Documentation:

Reference manual: tmbstan.pdf

Downloads:

Package source: tmbstan_1.0.91.tar.gz
Windows binaries: r-devel: tmbstan_1.0.91.zip, r-release: tmbstan_1.0.91.zip, r-oldrel: tmbstan_1.0.91.zip
macOS binaries: r-release (arm64): tmbstan_1.0.91.tgz, r-oldrel (arm64): tmbstan_1.0.91.tgz, r-release (x86_64): tmbstan_1.0.91.tgz, r-oldrel (x86_64): tmbstan_1.0.91.tgz
Old sources: tmbstan archive

Reverse dependencies:

Reverse imports: BayesGP, hmmTMB
Reverse suggests: SAMtool
Reverse enhances: dsem

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tmbstan to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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