Characterizing Markov equivalence classes for AMP chain graph models

DOI10.1214/009053606000000173zbMath1096.62097arXivmath/0607037OpenAlexW1970822905MaRDI QIDQ2497188

Michael D. Perlman, Steen Arne Andersson

Publication date: 3 August 2006

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0607037

zbMATH Keywords

chain graphgraphical modelMarkov equivalenceessential graph

Mathematics Subject Classification ID

Applications of graph theory (05C90) Graph theory (including graph drawing) in computer science (68R10) Special processes (60K99) Inference from stochastic processes (62M99) Knowledge representation (68T30) Markov processes (60J99) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items

Chain graphs for multilevel models, Sequences of regressions and their independences, On expressiveness of the chain graph interpretations, Learning marginal AMP chain graphs under faithfulness revisited, Learning AMP chain graphs and some marginal models thereof under faithfulness, Multiple testing and error control in Gaussian graphical model selection, AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms, Characterizing Markov equivalence classes for AMP chain graph models, Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property, Chain graph interpretations and their relations revisited

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