Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/105477
Title: Towards characterizing Markov equivalence classes for directed acyclic graphs with latent variables
Authors: Ali, R.A. 
Richardson, T.S.
Spirtes, P.
Zhang, J.
Keywords: DAG
Markov equivalence
Maximal ancestral graph
Issue Date: 2005
Citation: Ali, R.A.,Richardson, T.S.,Spirtes, P.,Zhang, J. (2005). Towards characterizing Markov equivalence classes for directed acyclic graphs with latent variables. Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005 : 10-17. ScholarBank@NUS Repository.
Abstract: It is well known that there may be many causal explanations that are consistent with a given set of data. Recent work has been done to represent the common aspects of these explanations into one representation. In this paper, we address what is less well known: how do the relationships common to every causal explanation among the observed variables of some DAG process change in the presence of latent variables? Ancestral graphs provide a class of graphs that can encode conditional independence relations that arise in DAG models with latent and selection variables. In this paper we present a set of orientation rules that construct the Markov equivalence class representative for ancestral graphs, given a member of the equivalence class. These rules are sound and complete. We also show that when the equivalence class includes a DAG, the equivalence class representative is the essential graph for the said DAG.
Source Title: Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005
URI: http://scholarbank.nus.edu.sg/handle/10635/105477
ISBN: 0974903914
Appears in Collections:Staff Publications

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