Markov Chain Monte Carlo sampling toolkit.

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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. pymc 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. pymc includes methods for summarizing output, plotting, goodness-of-fit and convergence diagnostics.

pymc only requires NumPy. All other dependencies such as matplotlib, SciPy, pytables, sqlite or mysql are optional.

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5.18.0

5.17.1 yanked

Reason this release was yanked:

It was a mistake, supposed to be 5.18.

5.17.0

5.16.2

5.16.1

5.16.0

5.15.1

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5.14.0

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4.0.0b6 pre-release

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4.0.0b3 pre-release

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2.3.8

2.3.6

2.3.5

2.3.4

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2.3.3

2.3.2

2.3.1

2.3

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2.1beta pre-release

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