On Sampling Strategies in Bayesian Variable Selection Problems With Large Model Spaces

DOI10.1080/01621459.2012.742443OpenAlexW1977944427MaRDI QIDQ4916951

Gonzalo García-Donato, Miguel A. Martinez-Beneito

Publication date: 26 April 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2012.742443

zbMATH Keywords

Bayesian model selection\(g\)-priorssearching strategies

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (18)

Bayesian inference of causal effects from observational data in Gaussian graphical models ⋮ Model Uncertainty Quantification in Cox Regression ⋮ Relevant parameter changes in structural break models ⋮ Bayesian Model Selection of Gaussian Directed Acyclic Graph Structures ⋮ Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression ⋮ Bayesian regularization via graph Laplacian ⋮ The Median probability model and correlated variables ⋮ Bayesian causal inference in probit graphical models ⋮ A loss-based prior for variable selection in linear regression methods ⋮ Equivalence class selection of categorical graphical models ⋮ Structural learning and estimation of joint causal effects among network-dependent variables ⋮ An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models ⋮ A model selection approach for variable selection with censored data ⋮ Inference From Intrinsic Bayes’ Procedures Under Model Selection and Uncertainty ⋮ Two-Stage Bayesian Approach for GWAS With Known Genealogy ⋮ Multiple changepoint detection with partial information on changepoint times ⋮ Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection ⋮ Mixtures ofg-Priors in Generalized Linear Models

Uses Software

• WinBUGS
• GSL
• SSS
• BayesVarSel
• SDaA

Cites Work

• Unnamed Item
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• Fully Bayes factors with a generalized \(g\)-prior
• Bayesian model averaging: A tutorial. (with comments and a rejoinder).
• Model uncertainty
• Markov chains for exploring posterior distributions. (With discussion)
• Practical Markov Chain Monte Carlo
• Objective Bayesian model selection in Gaussian graphical models
• Adaptive sampling for Bayesian variable selection
• Bayesian Modeling Using WinBUGS
• Mixtures of g Priors for Bayesian Variable Selection
• Marginal Likelihood From the Metropolis–Hastings Output
• Bayesian Graphical Models for Discrete Data
• Shotgun Stochastic Search for “Largep” Regression
• Posterior model probabilities via path‐based pairwise priors
• On finite population sampling theory under certain linear regression models
• Objective Bayesian Variable Selection
• On the Theory of Sampling from Finite Populations

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