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.

Bayesian Data Analysis demos for Python

RStan, the R interface to Stan

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

Bayesian analysis + tidy data + geoms (R package)

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

A collection of Bayesian data analysis recipes using PyMC3

How to do Bayesian statistical modelling using numpy and PyMC3

Bayesian Data Analysis demos for R

High-performance Bayesian Data Analysis on the GPU in Clojure

rstanarm R package for Bayesian applied regression modeling

shinystan R package and ShinyStan GUI

Statistical Rethinking with PyTorch and Pyro

Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)

Doing Bayesian statistics in Python!

🚫 ↩️ A document that introduces Bayesian data analysis.

'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)

Reproducing plots of Bayesian Data Analysis (Gelman et al, 3rd Edition) in Python

Stanマニュアルの日本語への翻訳プロジェクト

Bayesian Data Analysis demos for Matlab/Octave

The Birch probabilistic programming language.

Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.

Examples for Bayesian inference using DynamicHMC.jl and related packages.

Bayesian multilevel mediation models in R

Tools for Developing R Packages Interfacing with Stan

Bayesian Cost Effectiveness Analysis. Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators"). Produces many summary and plots to analyse the results

A compiler for Bayesian time series models.

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC