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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=latestemcee 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.