Contstructing a MarkovChain with MetropolisHastings is now working for Networks which consist only of LinearGaussian nodes or ProbabilityTables. Additionally it is now possible to specify the form of densityfunction that one expects for PosteriorMarginal. Learning a Gaussian from a MarkovChain is also possible
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| test_out.xmlbif |
This project contains probabilistic inference modules for Python. Our aim is to create a library which offers well known probabilistic (graphical) models like Bayesian or temporal networks. A variety of inference algorithms will be implemented soon.