Bayesian Analysis of Marginal Log-Linear Graphical Models for Three Way Contingency Tables

2008/07/07 by Ioannis Ntzoufras, Ntzoufras, Ioannis, Claudia Tarantola +1
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.0807.1001

openalex publication_date 2008/07/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper deals with the Bayesian analysis of graphical models of marginal independence for three way contingency tables. We use a marginal log-linear parametrization, under which the model is defined through suitable zero-constraints on the interaction parameters calculated within marginal distributions. We undertake a comprehensive Bayesian analysis of these models, involving suitable choices of prior distributions, estimation, model determination, as well as the allied computational issues. The methodology is illustrated with reference to two real data sets.

Citations

• Hyper Markov Laws in the Statistical Analysis of Decomposable Graphical Models

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