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Every LWF and AMP Chain Graph Originates from a Set of Causal Models
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
2015 (English)In: SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, ECSQARU 2015, SPRINGER-VERLAG BERLIN , 2015, Vol. 9161, 325-334 p.Conference paper, Published paper (Refereed)
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Abstract [en]

This paper aims at justifying LWF and AMP chain graphs by showing that they do not represent arbitrary independence models. Specifically, we show that every chain graph is inclusion optimal wrt the intersection of the independence models represented by a set of directed and acyclic graphs under conditioning. This implies that the independence model represented by the chain graph can be accounted for by a set of causal models that are subject to selection bias, which in turn can be accounted for by a system that switches between different regimes or configurations.

Place, publisher, year, edition, pages
SPRINGER-VERLAG BERLIN , 2015. Vol. 9161, 325-334 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 9161
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:liu:diva-123537DOI: 10.1007/978-3-319-20807-7_29ISI: 000364847800029ISBN: 978-3-319-20807-7; 978-3-319-20806-0 (print)OAI: oai:DiVA.org:liu-123537DiVA: diva2:886133
Conference
13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU)
Available from: 2015-12-21 Created: 2015-12-21 Last updated: 2015-12-21

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Citation style
  • apa
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Language
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  • asciidoc
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