The Python ensemble sampling toolkit for affine-invariant MCMC
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.
Read the docs at emcee.readthedocs.io.
Please cite Foreman-Mackey, Hogg, Lang & Goodman (2012) if you find this code useful in your research and add your paper to the testimonials list. 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}
}
Copyright 2010-2017 Dan Foreman-Mackey and contributors.
emcee is free software made available under the MIT License. For details see the LICENSE file.