Become a sponsor to Stan
Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation. 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 is a C++ package built on top of the Stan Math library, which provides
- 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.
There are interfaces available in R, Python, MATLAB, Julia, Stata, Mathematica, and for the command line.
Stan has a highly active development program with many volunteer contributors.
Stan Sponsorship
Funds contributed to the Stan project will be used for development, documentation and distribution of Stan software, and for technical and educational support for Stan users.
Current sponsors 7
Past sponsors 8
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stan-dev/pystan
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
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stan-dev/cmdstan
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stan-dev/stan
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
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stan-dev/rstanarm
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stan-dev/math
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic model…
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