Stan is a C++ and R package providing
- full Bayesian inference using the No-U-Turn sampler (NUTS), a variant of Hamiltonian Monte Carlo (HMC),
- approximate Bayesian inference using automatic differentiation variational inference (ADVI),
- penalized maximum likelihood estimation (MLE) using L-BFGS optimization,
- a full first- and higher-order automatic differentiation library based on C++ template overloads, and
- a supporting fully-templated matrix, linear algebra, and probability special function library.
Stan's home page, with links to everything you'll need to use Stan is:
There are separate repositories here on GitHub for interfaces:
- RStan (R interface)
- PyStan (Python interface)
- CmdStan (command-line/shell interface)
Stan's source-code repository is hosted here on GitHub.
The core Stan C++ code and CmdStan are licensed under new BSD. RStan and PyStan are licensed under GPLv3.