| Authors: | Anand Patil, David Huard, Christopher J. Fonnesbeck |
| Title: | [download] (4507)PyMC: Bayesian Stochastic Modelling in Python |
| Reference: | Vol. 35, Issue 4, Jul 2010 Submitted 2008-12-22, Accepted 2010-01-22 |
| Type: | Article |
| Abstract: | This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques. |
| Paper: | [download] (4507)PyMC: Bayesian Stochastic Modelling in Python (application/pdf, 1.2 MB) |
| Supplements: | [download] (397)pymc-2.1beta.tar.gz: Python source package (application/x-gzip, 1.2 MB) |
| [download] (390)v35i04.zip: Python example code from the paper (application/zip, 7 KB) |
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| Resources: | BibTeX | OAI |
