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Author: Daniel Foreman-Mackey

Maintainer: Daniel Foreman-Mackey

Classifiers

Development Status

5 - Production/Stable

Intended Audience

Developers
Science/Research

License

OSI Approved :: MIT License

Operating System

OS Independent

Programming Language

Python

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. 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}
}