Ancestral graph Markov models

• 成果类型: Article
• 署名作者: Richardson, T; Spirtes, P
• 署名单位: University of Washington; University of Washington Seattle; Florida Institute for Human & Machine Cognition (IHMC)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 2002
• 页码: 962-1030
• 关键词: conditional-independence; path diagrams

摘要

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.