Python interface to JAGS library for Bayesian data analysis.
PyJAGS: The Python Interface to JAGS
PyJAGS provides a Python interface to JAGS, a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.
PyJAGS adds the following features on top of JAGS:
- Multicore support for parallel simulation of multiple Markov chains (See Jupyter Notebook Advanced Functionality
- Saving sample MCMC chains to and restoring from HDF5 files
- Functionality to merge samples along iterations or across chains so that sampling can be resumed in consecutive chunks until convergence criteria are satisfied
- Connectivity to the Bayesian analysis and visualization package Arviz
PyJAGS works on MacOS and Linux. Windows is not currently supported.
A working JAGS installation is required.
- Package on the Python Package Index https://pypi.python.org/pypi/pyjags
- Project page on github https://github.com/michaelnowotny/pyjags
- JAGS manual and examples http://sourceforge.net/projects/mcmc-jags/files/
- JAGS was created by Martyn Plummer
- PyJAGS was originally created by Tomasz Miasko
- As of May 2020, PyJAGS is developed by Michael Nowotny
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