emcee

emcee

The Python ensemble sampling toolkit for affine-invariant MCMC

.. image:: https://img.shields.io/badge/GitHub-dfm%2Femcee-blue.svg?style=flat :target: https://github.com/dfm/emcee .. image:: https://github.com/dfm/emcee/workflows/Tests/badge.svg :target: https://github.com/dfm/emcee/actions?query=workflow%3ATests .. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat :target: https://github.com/dfm/emcee/blob/main/LICENSE .. image:: http://img.shields.io/badge/arXiv-1202.3665-orange.svg?style=flat :target: https://arxiv.org/abs/1202.3665 .. image:: https://coveralls.io/repos/github/dfm/emcee/badge.svg?branch=main&style=flat&v=2 :target: https://coveralls.io/github/dfm/emcee?branch=main .. image:: https://readthedocs.org/projects/emcee/badge/?version=latest :target: http://emcee.readthedocs.io/en/latest/?badge=latest

emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010) <http://cims.nyu.edu/~weare/papers/d13.pdf>_. The code is open source and has already been used in several published projects in the Astrophysics literature.

Documentation

Read the docs at emcee.readthedocs.io <http://emcee.readthedocs.io/>_.

Attribution

Please cite Foreman-Mackey, Hogg, Lang & Goodman (2012) <https://arxiv.org/abs/1202.3665>_ if you find this code useful in your research. The BibTeX entry for the paper is::

@article{emcee,
   author = {{Foreman-Mackey}, D. and {Hogg}, D.~W. and {Lang}, D. and {Goodman}, J.},
    title = {emcee: The MCMC Hammer},
  journal = {PASP},
     year = 2013,
   volume = 125,
    pages = {306-312},
   eprint = {1202.3665},
      doi = {10.1086/670067}
}

License

Copyright 2010-2021 Dan Foreman-Mackey and contributors.

emcee is free software made available under the MIT License. For details see the LICENSE file.