Bayesian model determination for multivariate ordinal and binary data

DOI10.1016/j.csda.2007.09.008zbMath1452.62232OpenAlexW2054579098WikidataQ58296085 ScholiaQ58296085MaRDI QIDQ1023593

Jonathan J. Forster, Emily L. Webb

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.008

zbMATH Keywords

reversible jump MCMCgraphical modelordinal probit model

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Probabilistic graphical models (62H22)

Related Items

Bayesian model choice in cumulative link ordinal regression models, A fully nonparametric modeling approach to binary regression, Bayesian Variable Selection for Gaussian Copula Regression Models, Bayesian nonparametric density autoregression with lag selection, A Bayesian nonparametric Markovian model for non-stationary time series, Unnamed Item, Cholesky-GARCH models with applications to finance, Conditional independence of multivariate binary data with an application in caries research, Bayesian Nonparametric Modeling for Multivariate Ordinal Regression

Uses Software

• WinBUGS
• MIM

Cites Work

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• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Schur products and matrix completions
• Hyper Markov laws in the statistical analysis of decomposable graphical models
• Markov chain Monte Carlo model selection for DAG models
• Generating and characterizing the perfect elimination orderings of a chordal graph
• Properties of prior and posterior distributions for multivariate categorical response data models
• Incorporating Prior Information into the Analysis of Contingency Tables
• Bayesian Multivariate Logistic Regression
• A fast procedure for model search in multidimensional contingency tables
• Analysis of multivariate probit models
• On the Application of Conditional Independence to Ordinal Data
• Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
• Bayesian analysis of covariance matrices and dynamic models for longitudinal data
• Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
• Parsimonious Covariance Matrix Estimation for Longitudinal Data
• Introduction to Graphical Modelling
• The Grouped Continuous Model for Multivariate Ordered Categorical Variables and Covariate Adjustment
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
• Cholesky decomposition of a hyper inverse Wishart matrix
• Bayesian Analysis of Binary and Polychotomous Response Data
• Model Determination for Categorical Data With Factor Level Merging