A Factorization Criterion for Acyclic Directed Mixed Graphs
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) dseparation.
Cite
Text
Richardson. "A Factorization Criterion for Acyclic Directed Mixed Graphs." Conference on Uncertainty in Artificial Intelligence, 2009.Markdown
[Richardson. "A Factorization Criterion for Acyclic Directed Mixed Graphs." Conference on Uncertainty in Artificial Intelligence, 2009.](https://mlanthology.org/uai/2009/richardson2009uai-factorization/)BibTeX
@inproceedings{richardson2009uai-factorization,
title = {{A Factorization Criterion for Acyclic Directed Mixed Graphs}},
author = {Richardson, Thomas S.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2009},
pages = {462-470},
url = {https://mlanthology.org/uai/2009/richardson2009uai-factorization/}
}