Stratified graphical models -- context-specific independence in graphical models

DOI10.1214/14-BA882zbMath1327.62030arXiv1409.2262MaRDI QIDQ899060

Jukka Corander, Timo Koski, Johan Pensar, Henrik Nyman

Publication date: 21 December 2015

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1409.2262

zbMATH Keywords

Markov chain Monte Carlographical modelcontext-specific interaction modelmultivariate discrete distributionBayesian model learning

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Bayesian inference (62F15) Graphical methods in statistics (62A09)

Related Items

Context-specific independence in graphical log-linear models ⋮ Marginal and simultaneous predictive classification using stratified graphical models ⋮ Context-specific independencies in hierarchical multinomial marginal models ⋮ Learning discrete decomposable graphical models via constraint optimization ⋮ Structure Learning of Contextual Markov Networks using Marginal Pseudo‐likelihood ⋮ Context-Specific and Local Independence in Markovian Dependence Structures ⋮ Bayesian Graphical Regression

Uses Software

• UCI-ml

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