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Markov properties for mixed graphs

Abstract:
In this paper, we unify the Markov theory of a variety of different types of graphs used in graphical Markov models by introducing the class of loopless mixed graphs, and show that all independence models induced by $m$-separation on such graphs are compositional graphoids. We focus in particular on the subclass of ribbonless graphs which as special cases include undirected graphs, bidirected graphs, and directed acyclic graphs, as well as ancestral graphs and summary graphs. We define maximality of such graphs as well as a pairwise and a global Markov property. We prove that the global and pairwise Markov properties of a maximal ribbonless graph are equivalent for any independence model that is a compositional graphoid.
Publication status:
Published

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Publisher copy:
10.3150/12-BEJ502

Authors



Publisher:
International Statistical Institute
Journal:
Bernoulli More from this journal
Volume:
20
Issue:
2
Pages:
676-696
Publication date:
2011-09-27
DOI:
ISSN:
1350-7265


Language:
English
Keywords:
Pubs id:
pubs:184652
UUID:
uuid:72e6b348-88e1-417b-a77a-bd8bf4ca7edb
Local pid:
pubs:184652
Source identifiers:
184652
Deposit date:
2012-12-20

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