A factorization criterion for acyclic directed mixed graphs
Artificial Intelligence
2014-06-27 v1
Abstract
Acyclic directed mixed graphs, also known as semi-Markov models represent the conditional independence structure induced on an observed margin by a DAG model with latent variables. In this paper we present a factorization criterion for these models that is equivalent to the global Markov property given by (the natural extension of) d-separation.
Cite
@article{arxiv.1406.6764,
title = {A factorization criterion for acyclic directed mixed graphs},
author = {Thomas S. Richardson},
journal= {arXiv preprint arXiv:1406.6764},
year = {2014}
}
Comments
Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI2009)