https://github.com/dfm/emcee

The Python ensemble sampling toolkit for affine-invariant MCMC
https://github.com/dfm/emcee

mcmc mcmc-sampler probabilistic-data-analysis python

Last synced: 10 days ago
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The Python ensemble sampling toolkit for affine-invariant MCMC

• Host: GitHub
• URL: https://github.com/dfm/emcee
• Owner: dfm
• License: mit
• Created: 2011-11-07T16:17:08.000Z (about 13 years ago)
• Default Branch: main
• Last Pushed: 2024-05-02T00:41:56.000Z (6 months ago)
• Last Synced: 2024-05-22T14:41:18.885Z (6 months ago)
• Topics: mcmc, mcmc-sampler, probabilistic-data-analysis, python
• Language: Python
• Homepage: https://emcee.readthedocs.io
• Size: 32.8 MB
• Stars: 1,430
• Watchers: 87
• Forks: 431
• Open Issues: 55
• Metadata Files:
  • Readme: README.rst
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Authors: AUTHORS.rst

Awesome Lists containing this project

• awesome-sciml - dfm/emcee: The Python ensemble sampling toolkit for affine-invariant MCMC
• awesome-list - emcee - The Python ensemble sampling toolkit for affine-invariant Markov chain Monte Carlo (MCMC). (Linear Algebra / Statistics Toolkit / Statistical Toolkit)

README

        
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) `_.

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 `_.

Attribution

-----------

Please cite `Foreman-Mackey, Hogg, Lang & Goodman (2012)

`_ 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.