ways to run Stan
The Stan modeling language and statistical algorithms are exposed through interfaces into many popular computing environments.
CmdStan (shell, command-line terminal)
CmdStanR (R, lightweight wrapper for CmdStan)
CmdStanPy (Python, lightweight wrapper for CmdStan)
Programs written in the Stan modeling language are portable across interfaces.
RStanArm and brms provide R formula interfaces that automate regression modeling.
The main differences between these packages are that RStanArm uses precompiled models whereas brms compiles on the fly, and that they support slightly different classes of models and automated posterior analyses; both allow raw Stan output to be recovered and used directly.
The Stan Math Library provides differentiable special functions, probability densities, and linear algebra in C++.
Stan Math Library (C++)
The Stan Core Library includes the language source-to-source compiler, I/O, inference algorithms, and posterior analysis algorithms, all in C++.
ShinyStan provides interactive visual summaries and advanced posterior analysis of MCMC output.
The bayesplot package is a ggplot2-based plotting library for graphing parameter estimates, MCMC diagnostics, and posterior predictive checks.
The rstantools package provides various tools for developers of R packages interfacing with Stan.
The loo package provides efficient leave-one-out cross-validation and WAIC calculations.
Stan Language Syntax Aware Editors
RStudio now recognizes
.stan files and provides syntax highlighting,
formatting, and checking.
Vim has several plugins that offer syntax highlighting and support for Stan.
Atom has a language definition plugin for Stan, which also provides the highlighting seen on GitHub.
This highlighting is also the one used by the pandoc tool used by RMarkdown.