文章基本信息

标题：The dynamic chain event graph
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作者：Lorna M. Barclay ; Rodrigo A. Collazo ; Jim Q. Smith 等
期刊名称：Electronic Journal of Statistics
印刷版ISSN：1935-7524
出版年度：2015
卷号：9
期号：2
页码：2130-2169
DOI：10.1214/15-EJS1068
语种：English
出版社：Institute of Mathematical Statistics
摘要：In this paper we develop a formal dynamic version of Chain Event Graphs (CEGs), a particularly expressive family of discrete graphical models. We demonstrate how this class links to semi-Markov models and provides a convenient generalization of the Dynamic Bayesian Network (DBN). In particular we develop a repeating time-slice Dynamic CEG providing a useful and simpler model in this family. We demonstrate how the Dynamic CEG’s graphical formulation exhibits asymmetric conditional independence statements and also how each model can be estimated in a closed form enabling fast model search over the class. The expressive power of this model class together with its estimation is illustrated throughout by a variety of examples that include the risk of childhood hospitalization and the efficacy of a flu vaccine.
关键词：Chain Event Graphs;Markov processes;proba bilistic graphical models;dynamic Bayesian networks.