An assistant for using pyjags
Bayesian Cognitive Modeling with
This is a project to port the code examples in Lee and Wagenmakers' 2013 textbook Bayesian Cognitive Modeling: A Practical Course from MATLAB into Python, using the pyjags package for interfacing Python code with the
JAGS Gibbs sampling application.
The main contribution is the module
pjbcmassistant, which contains convenience classes
SampleHandler for easily interfacing with
pyjags, and for performing basic analysis on the model samples it produces.
The notebook PyJAGS-BCM Usage Guide provides a demonstration and overview of how to use the module for building and analyzing models.
See the full documentation for details on all methods provided by the module.
In addition to dependencies listed in requirements.txt, this module requires that
JAGS (which is not a Python package) be successfully installed on your system prior to configuring
pyjags. See the JAGS website and the pyjags installation instructions for details.
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