On sampling graphical Markov models
Probability
2017-08-16 v2 Combinatorics
Abstract
We consider sampling and enumeration problems for Markov equivalence classes. We create and analyze a Markov chain for uniform random sampling on the DAGs inside a Markov equivalence class. Though the worst case is exponentially slow mixing, we find a condition on the Markov equivalence class for polynomial time mixing. We also investigate the ratio of Markov equivalence classes to DAGs and a Markov chain of He, Jia, and Yu for random sampling of sparse Markov equivalence classes.
Cite
@article{arxiv.1705.09717,
title = {On sampling graphical Markov models},
author = {Megan Bernstein and Prasad Tetali},
journal= {arXiv preprint arXiv:1705.09717},
year = {2017}
}