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pymc 2.2

Markov Chain Monte Carlo sampling toolkit.

Latest Version: 2.3.2

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.

 
File Type Py Version Uploaded on Size
pymc-2.2-py2.6-linux-x86_64.egg (md5) Python Egg 2.6 2012-05-07 1MB
pymc-2.2-py2.7-macosx-10.7-intel.egg (md5) Python Egg 2.7 2012-05-07 1000KB
pymc-2.2-py2.7-win32.egg (md5)
Built with EPD 7.2
Python Egg 2.7 2012-05-07 1MB
pymc-2.2.tar.gz (md5) Source 2012-05-08 343KB
pymc-2.2.win32-py2.7.exe (md5)
Built with EPD 7.2.2 compilers
MS Windows installer 2.7 2012-07-12 1MB
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