A Bayesian Approach to the Estimation of Expected Cell Counts by Using Log-Linear Models

DOI10.1080/03610920500439927zbMath1084.62022OpenAlexW2042112052MaRDI QIDQ5201493

Canan Hamurkaroglu, Haydar Demirhan

Publication date: 19 April 2006

Published in: Communications in Statistics: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920500439927

zbMATH Keywords

hierarchical modelingGibbs samplingmultivariate normal distributionlog-linear modelBayesian posterior estimateslog-normal priormultivariate log-normal distributionexpected cell countsGeweke's modified \(z\)-test

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items (1)

A Bayesian approach for the estimation of probability distributions under finite sample space

Cites Work

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• Bayesian log linear estimates for three-way contingency tables
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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