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Algorithms for exploring Markov equivalence classes: MCMC, size counting

Project description

This package provides functions for sampling from a space of Markov equivalence classes of directed acyclic graphs via a reversible MCMC, and for counting and exploring sizes of these classes.

Example:

pip install ./MarkovEquClasses-1.0.zip

import MarkovEquClasses

MarkovEquClasses.smalldemo()

People who use the codes should ack the author and cite the papers in the following Reference.

Reference:

Yangbo He and Jinzhu Jia and Bin Yu, Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs, The Annals of Statistics,41(1),1742-1779,2013.

Yangbo He and Jinzhu Jia and Bin Yu, Supplement to “Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs”,2013.[http://arxiv.org/abs/1303.0632]

Yangbo He and Jinzhu Jia and Bin Yu, Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs,To appear in Journal of machine learning research, 2015

Project details


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Files for MarkovEquClasses, version 1.0
Filename, size File type Python version Upload date Hashes
Filename, size MarkovEquClasses-1.0.1.zip (14.3 kB) File type Source Python version None Upload date Hashes View

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