There are 22 repositories under bayesian-data-analysis topic.
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 course at Aalto
Bayesian Data Analysis demos for Python
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
How to do Bayesian statistical modelling using numpy and PyMC3
Bayesian Data Analysis demos for R
A collection of Bayesian data analysis recipes using PyMC3
High-performance Bayesian Data Analysis on the GPU in Clojure
Statistical Rethinking with PyTorch and Pyro
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Exploring and eliciting probability distributions
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.
Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, Vasishth
:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
Solutions and workflow for the Bayesian Statistics The Fun Way book in Python
Doing Bayesian statistics in Python!
'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
Bayesian Data Analysis demos for Matlab/Octave
Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.
priorsense: an R package for prior diagnostics and sensitivity
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 common framework for implementing and using log densities for inference.
Examples for Bayesian inference using DynamicHMC.jl and related packages.
Make a sweet giant triangle confusogram (GTC) plot
Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC
Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation