The Python ensemble sampling toolkit for MCMC
Project description
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.
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 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} }
License
Copyright 2010-2019 Dan Foreman-Mackey and contributors.
emcee is free software made available under the MIT License. For details see the LICENSE file.
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