Stan
Website
Social Media
Twitter: @mcmc_stan
Description
Thousands of users rely on Stan for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.
Users specify log density functions in Stan’s probabilistic programming language and get:
- full Bayesian statistical inference with MCMC sampling (NUTS, HMC)
- approximate Bayesian inference with variational inference (ADVI)
- penalized maximum likelihood estimation with optimization (L-BFGS)
Stan’s math library provides differentiable probability functions & linear algebra (C++ autodiff). Additional R packages provide expression-based linear modeling, posterior visualization, and leave-one-out cross-validation.
Languages
Stan, C++, Shell, R Language
Team
Leadership Team:
All financial decisions related to NumFOCUS are made by Stan’s Leadership Body for NumFOCUS:
- Michael Betancourt (Columbia University)
- Tamara Broderick (Massachusetts Institute of Technology)
- Bob Carpenter (Columbia University)
- Andrew Gelman (Columbia University)
- Elizabeth Wolkovich (Harvard University)
Governance
Code of Conduct
Code Repository
GitHub: Stan Organization
Build Tools
Packages
Releases
Various, see Stan - Interfaces
Issue Tracker
Various, all hosted on GitHub.
Documentation
Contributing:
- Developer process overview · stan-dev/stan Wiki
- Interfaces: Stan - Interfaces
- Overview: Stan - Documentation
Community
Discussion
- Dev MailingList: stan development mailing list - Google Groups
- Discourse: The Stan Forums
- User MailingList: Stan users mailing list - Google Groups
Events
License
Combo of BSD-3-Clause, GPLv3: stan/licenses at develop · stan-dev/stan