rstan: R Interface to Stan

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

Package details

AuthorJiqiang Guo [aut], Jonah Gabry [aut], Ben Goodrich [cre, aut], Andrew Johnson [aut], Sebastian Weber [aut], Hamada S. Badr [aut] (<https://orcid.org/0000-0002-9808-2344>), Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Modrak Martin [ctb], Trustees of Columbia University [cph], Oleg Sklyar [cph] (R/cxxfunplus.R), The R Core Team [cph] (R/pairs.R, R/dynGet.R), Jens Oehlschlaegel-Akiyoshi [cph] (R/pairs.R), John Maddock [cph] (gamma.hpp), Paul Bristow [cph] (gamma.hpp), Nikhar Agrawal [cph] (gamma.hpp), Christopher Kormanyos [cph] (gamma.hpp), Bronder Steve [ctb]
MaintainerBen Goodrich <benjamin.goodrich@columbia.edu>
LicenseGPL (>= 3)
Version2.32.3
URL https://mc-stan.org/rstan/ https://discourse.mc-stan.org
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("rstan")

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rstan documentation built on Oct. 15, 2023, 9:06 a.m.