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Faithfulness in Chain Graphs: The Gaussian Case
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology. (ADIT)
2011 (English)In: Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS 2011), MIT Press, 2011, , 588-599 p.588-599 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper deals with chain graphs under the classic Lauritzen-Wermuth-Frydenberg interpretation. We prove that almost all the regular Gaussian distributions that factorize with respect to a chain graph are faithful to it. This result has three important consequences. First, chain graphs are more powerful than undirected graphs and acyclic directed graphs for representing regular Gaussian distributions, as some of these distributions can be represented exactly by the former but not by the latter. Second, the moralization and c-separation criteria for reading independencies from a chain graph are complete, in the sense that they identify all the independencies that can be identified from the chain graph alone. Third, some definitions of equivalence in chain graphs coincide and, thus, they have the same graphical characterization.

Place, publisher, year, edition, pages
MIT Press, 2011. , 588-599 p.588-599 p.
Series
JMLR: Workshop and Conference Proceedings, ISSN 1938-7228 ; 15
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-74540OAI: oai:DiVA.org:liu-74540DiVA: diva2:487636
Conference
14th International Conference on Artificial Intelligence and Statistics (AISTATS 2011)
Available from: 2012-01-31 Created: 2012-01-31 Last updated: 2015-05-28

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Peña, Jose M.

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