The Python ensemble sampling toolkit for affine-invariant MCMC

MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice

Pythonic stellar model grid access; easy MCMC fitting of stellar properties

A list of Python-based MCMC & ABC packages

Parallel tempering MCMC sampler package written in Python

Create Your Own Metropolis-Hastings Markov Chain Monte Carlo Algorithm for Bayesian Inference (With Python)

High-performance C++ framework for afterglow modeling with Python bindings. Features fast multi-wavelength light curve generation, MCMC parameter inference, and advanced physics models including shock dynamics, radiation mechanisms, and structured jets. Designed for computational efficiency and scientific workflow integration.

Python MCMC Sampler

Markov Chain Monte Carlo MCMC methods are implemented in various languages (including R, Python, Julia, Matlab)

ELISa (Eclipsing binary Learning and Interactive System) is a Python-based tool designed for efficient modeling of light and radial velocity curves of eclipsing binaries. It balances computational speed and accuracy, offering modular, cross-platform usability and built-in optimization methods like least squares and MCMC for parameter determination.

A Python tool to make interactive Corner Plots based on XSPEC MCMC chains saved to FITS files.

Adaptive MCMC and CMA-ES Python code

This is a python tutorial for Bayesian inferences using MCMC. It includes concepts of reject sampling, markov chain stationary distribution, and uses Python package pymc.

Python MCMC

Python package dedicated to the planet orbit fitting using MCMC approach.

「ゼロからできるMCMC」をPythonで実装するリポジトリ

Python implementation of MCMC algorithm for estimation of spatial negative binomial model with Bayesian additive regression trees

Code to analyse the BOSS dataset including measurement of the power spectrum and covariance matrix. I also show how to derive a likelihood using MCMC. Based on the python packages nbodykit and emcee.

Python code for likelihood analysis and MCMC posterior sampling of void-galaxy cross-correlation data

A demonstration of various Python MCMC samplers

Pure Python Hamiltonian MCMC sampler

A Python package for Modified Gravity MCMC simulations.

Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC). A python numpy implementation of mcmcse.r

Python bindings for MCMC diagnostics using coda in R

Developing statistical models on Python to describe the fluctuations of tick-by-tick single asset price moves (microstructure noise) : Markov renewal processes, Poisson Processes, Brownian motion. Rare event probability estimation through importance sampling, MCMC/Splitting and interacting particules methods.

GPplus is a probabilistic framework with a fast MCMC-GP python implementation to model generic features and their spatial correlations.

Minimal IMAP MCMC is a rapid Bayesian approach to Causal Structure Learning. It is in Python. In collaboration with Tamara Broderick's lab and based on algorithm by Raj Agrawal

MCMC diagnostics in Python

Markov chain Monte Carlo methods in Python

Slice sampling MCMC in Python