首页    期刊浏览 2024年07月05日 星期五
登录注册

文章基本信息

  • 标题:THE GRAPHICAL CONDITION FOR IDENTIFYING ARROWS IN RECOVERING CAUSAL STRUCTURE
  • 本地全文:下载
  • 作者:Manabu Kuroki ; Tomoyoshi Kikuchi ; Masami Miyakawa
  • 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
国家哲学社会科学文献中心版权所有