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The pymcmcstat package is a Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the ability to use different Metropolis based sampling techniques:

  • Metropolis-Hastings (MH): Primary sampling method.
  • Adaptive-Metropolis (AM): Adapts covariance matrix at specified intervals.
  • Delayed-Rejection (DR): Delays rejection by sampling from a narrower distribution. Capable of n-stage delayed rejection.
  • Delayed Rejection Adaptive Metropolis (DRAM): DR + AM

This package is an adaptation of the MATLAB toolbox mcmcstat. The user interface is designed to be as similar to the MATLAB version as possible, but this implementation has taken advantage of certain data structure concepts more amenable to Python.

Note, advanced plotting routines are available in the mcmcplot package. Many plotting features are directly available within pymcmcstat, but some user’s may find mcmcplot useful.


This code can be found on the Github project page. This package is available on the PyPI distribution site and the latest version can be installed via

pip install pymcmcstat

The master branch on Github typically matches the latest version on the PyPI distribution site. To install the master branch directly from Github,

pip install git+

You can also clone the repository and run python install.

Getting Started




See the GitHub contributor page

Citing pymcmcstat

Please see the pymcmcstat homepage or follow the DOI badge above to find the appropriate citation information.


Indices and tables