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Python interface to JAGS library for Bayesian data analysis.

Project description

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

License: GPLv2

Supported Platforms

PyJAGS works on MacOS and Linux. Windows is not currently supported.

Installation

A working JAGS installation is required.

    pip install pyjags

Useful Links

Acknowledgements

  • 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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