Title

A transformational characterization of Markov equivalence for directed acyclic graphs with latent variables

Document Type

Book chapter

Source Publication

Proceedings of the Twenty-First Conference Conference on Uncertainty in Artificial Intelligence (2005)

Publication Date

1-1-2005

First Page

667

Last Page

674

Publisher

AUAI Press

Abstract

Different directed acyclic graphs (DAGs) may be Markov equivalent in the sense that they entail the same conditional independence relations among the observed variables. Chickering (1995) provided a transformational characterization of Markov equivalence for DAGs (with no latent variables), which is useful in deriving properties shared by Markov equivalent DAGs, and, with certain generalization, is needed to prove the asymptotic correctness of a search procedure over Markov equivalence classes, known as the GES algorithm. For DAG models with latent variables, maximal ancestral graphs (MAGs) provide a neat representation that facilitates model search. However, no transformational characterization -- analogous to Chickering's -- of Markov equivalent MAGs is yet available. This paper establishes such a characterization for directed MAGs, which we expect will have similar uses as it does for DAGs.

Publisher Statement

Copyright © UAI 2005, AUAI Press.

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Additional Information

ISBN of the source publication: 0974903914

Full-text Version

Publisher’s Version

Recommended Citation

Zhang, J. & Spirtes, P. (2005). A transformational characterization of Markov equivalence for directed acyclic graphs with latent variables. In F. Bacchus & T. Jaakkola (Eds.), Proceedings of the Twenty-First Conference Conference on Uncertainty in Artificial Intelligence (2005) (pp.667-674). Arlington, Virginia: AUAI Press. Retrieved from https://dslpitt.org/uai/papers/05/p667-zhang.pdf