Ancestral graph Markov models
The Annals of StatisticsPublished 1 August 2002
Thomas S. Richardson, Peter Spirtes
Citations544
SJR quartileQ1
SJR score4.77
SNIP3.13
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TL;DR
A class of graphical independence models that is closed under marginalization and conditioning but that contains all DAG independence models, called maximal ancestral graphs, which lead to a simple parametrization of the corresponding set of distributions in the Gaussian case.
Abstract
This paper introduces a class of graphical independence models that is closed under marginalization and conditioning but that contains all DAG independence models. This class of graphs, called maximal ancestral graphs, has two attractive features: there is at most one edge between each pair of vertices; every missing edge corresponds to an independence relation. These features lead to a simple parameterization of the corresponding set of distributions in the Gaussian case.
Keywords
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