Parametrizations and reference priors for multinomial decomposable graphical models

DOI10.1016/j.jmva.2011.08.001zbMath1236.62011OpenAlexW1986335251MaRDI QIDQ764506

Publication date: 13 March 2012

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2011.08.001

zbMATH Keywords

natural exponential family cut clique conjugate family contingency tables log-linear models reference priors multinomial models

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15) Applications of graph theory (05C90) Contingency tables (62H17)

Related Items (1)

Bayesian model comparison based on expected posterior priors for discrete decomposable graphical models

Cites Work

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Improving on the maximum likelihood estimators of the means in Poisson decomposable graphical models
Bayes admissible estimation of the means in Poisson decomposable graphical models
The formal definition of reference priors
A conjugate prior for discrete hierarchical log-linear models
Admissible estimation, Dirichlet principles and recurrence of birth-death chains on \({\mathbb{Z}}^ p_+\)
Admissible and minimax estimation for the multinomial distribution and for k independent binomial distributions
Hyper Markov laws in the statistical analysis of decomposable graphical models
Stratified exponential families: Graphical models and model selection
Prior induction in log-linear models for general contingency table analysis.
Invariance of the reference prior under reparametrization
On the invariance of noninformative priors
Conditionally Reducible Natural Exponential Families and Enriched Conjugate Priors
Conjugate Parameterizations for Natural Exponential Families
Collapsibility and response variables in contingency tables
A fast procedure for model search in multidimensional contingency tables
Ordered group reference priors with application to the multinomial problem
Conjugate Priors for Exponential Families Having Quadratic Variance Functions
On the Markov Equivalence of Chain Graphs, Undirected Graphs, and Acyclic Digraphs
Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
The admissibility of the maximum likelihood estimator for decomposable log-linear interaction models for contingency tables
Bayesian Analysis: A Look at Today and Thoughts of Tomorrow
Bayesian Graphical Models for Discrete Data
Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
Model Determination for Categorical Data With Factor Level Merging
Reference priors for discrete graphical models
The case for objective Bayesian analysis

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