Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. pymc3 is a python package that implements the Metropolis-Hastings algorithm as a python class, and is extremely flexible and applicable to a large suite of problems. pymc3 includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|File Name & Checksum SHA256 Checksum Help||Version||File Type||Upload Date|
|pymc3-3.2-py3-none-any.whl (1.2 MB) Copy SHA256 Checksum SHA256||3.6||Wheel||Oct 10, 2017|
|pymc3-3.2.tar.gz (41.4 MB) Copy SHA256 Checksum SHA256||–||Source||Oct 10, 2017|