Jump to:
Stan is a statistical modeling language along with inference algorithms for full
Bayesian inference, approximate Bayesian inference, and penalized maximum likelihood
estimation. Stan is implemented in C++ but we provide interfaces for the
command line, R and Python (and more).
rstan
The rstan package is the R interface to Stan.
website |
CRAN |
source code on GitHub
rstanarm
The rstanarm package is for Bayesian applied regression modeling (ARM) via Stan.
It is an appendage to the rstan package that enables some of the
most common applied regression models to be estimated using Markov Chain
Monte Carlo, variational approximations to the posterior distribution, or
optimization. The rstanarm package allows these models to be
specified using the customary R modeling syntax (e.g., like that of
glm
with a formula
and a data.frame
).
website |
CRAN |
source code on GitHub
shinystan
The shinystan R package provides a graphical user interface providing
interactive visual and numerical summaries of model parameters and convergence
diagnostics for Bayesian models estimated using MCMC.
website |
CRAN |
source code on GitHub
bayesplot
The bayesplot R package provides a library of plotting functions for use
after fitting Bayesian models (typically with MCMC).
website |
CRAN |
source code on GitHub
A paper about bayesplot and visualization in the Bayesian workflow more generally:
loo
The loo R package is for efficient approximate leave-one-out cross-validation for Bayesian models.
website |
CRAN |
source code on GitHub
The package implements the methods described in these papers with Aki and Andrew:
Aki Vehtari, Andrew Gelman, and Jonah Gabry. (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing. 27(5), pp 1413-1432. (link to published version) | arXiv preprint arxiv:1507.04544
Aki Vehtari, Andrew Gelman, and Jonah Gabry. (2016). Pareto smoothed importance sampling. arXiv preprint arxiv:1507.02646
rstantools
The rstantools R package provides tools for developing R packages interfacing with Stan.
website |
CRAN |
source code on GitHub
posterior
The posterior R package provides efficient conversion between many different useful formats
of draws (samples) from posterior or prior distributions, consistent methods for operations commonly
performed on draws, various summaries of draws in convenient formats, and lightweight implementations
of state of the art posterior inference diagnostics.
website |
CRAN |
source code on GitHub
cmdstanr
The cmdstanr R package provides an R interface to CmdStan.
website | source code on GitHub
Preprints:
A selection of tutorial vignettes on practical topics in Bayesian data analysis.