文章基本信息

标题：THE GRAPHICAL CONDITION FOR IDENTIFYING ARROWS IN RECOVERING CAUSAL STRUCTURE
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作者：Manabu Kuroki ; Tomoyoshi Kikuchi ; Masami Miyakawa 等
期刊名称：JOURNAL OF THE JAPAN STATISTICAL SOCIETY
印刷版ISSN：1882-2754
电子版ISSN：1348-6365
出版年度：2001
卷号：31
期号：2
页码：175-185
DOI：10.14490/jjss1995.31.175
出版社：JAPAN STATISTICAL SOCIETY
摘要：This paper deals with problems of recovering a causal structure by using not only conditional independence relationships but also prior knowledge when data are generated according to the causal structure among variables. Although some algorithms for recovering a causal structure based on independencies have been developed, the influence of prior knowledge on the recovery algorithms has not been clarified. In this paper, a necessary and sufficient condition for the existence on unidentified arrows in a recovered diagram is given in terms of graph structure. Also, it is shown that a causal structure such that a recovered diagram is a forest can be recovered by recognizing exogenous variables in a causal diagram completely. The result enables us to elucidate enough prior information to determine a causal diagram uniquely.
关键词：exogenous variable;faithfulness;maximally oriented pattern;observational equivalence;orientation rules;pattern