Stan.

Stan: Open-Source Probabilistic Programming Language

An open-source probabilistic programming language for statistical modeling and data analysis, enabling simple model specification and executable program generation for inference and prediction.

What is Stan.?

Stan is an open-source probabilistic programming language used for Bayesian statistical modeling and data analysis. It allows users to specify statistical models using an intuitive modeling language, then automatically generates efficient C++ code to perform Bayesian inference. Some key features and benefits of Stan include:

- Flexible modeling language to specify a wide range of statistical models including generalized linear models, hierarchical models, mixture models, and more.

- Stochastic sampling algorithms like Hamiltonian Monte Carlo, variational inference, and others to perform full Bayesian inference on models.

- Compilation of models down to optimized C++ code for efficient sampling and inference.

- Interfaces with R, Python, MATLAB, Julia, Stata, and other platforms.

- Enables fitting complex Bayesian models that would be infeasible with standard tools.

- Modular modeling to reuse common model components and structures.

- Facilitates statistical inference tasks like parameter estimation, prediction, experimental design, and others.

- Active development community with documentation and resources for learning and applying Stan.

Overall, Stan empowers Bayesian modeling and inference for complex data analyses across statistics, machine learning, and the sciences.

Stan. Features

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