Marginal parameterizations of discrete models defined by a set of conditional independencies

DOI10.1016/j.jmva.2010.07.001zbMath1229.62064OpenAlexW2134364324MaRDI QIDQ604366

Sumit K. Garg

Publication date: 10 November 2010

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2010.07.001

zbMATH Keywords

smoothnessgraphical modelscompatibilitymarginal log-linear modelsmixed parameterizations

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Generalized linear models (logistic models) (62J12) Characterization and structure theory of statistical distributions (62E10) Contingency tables (62H17)

Related Items (5)

A class of smooth models satisfying marginal and context specific conditional independencies ⋮ Two algorithms for fitting constrained marginal models ⋮ Smoothness of conditional independence models for discrete data ⋮ Probability based independence sampler for Bayesian quantitative learning in graphical log-linear marginal models ⋮ Smoothness of marginal log-linear parameterizations

Cites Work

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• Discrete chain graph models
• Marginal models for categorical data
• Multivariate logistic models
• Marginal log-linear parameterization of conditional independence models
• A NOTE ON MULTIVARIATE LOGISTIC MODELS FOR CONTINGENCY TABLES
• Compatibility among marginal densities

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