Bayesian structured variable selection in linear regression models

DOI10.1007/s00180-014-0529-7zbMath1342.65065OpenAlexW1972155625WikidataQ58045647 ScholiaQ58045647MaRDI QIDQ737001

Min Wang, Tao Lü, Xiaoqian Sun

Publication date: 5 August 2016

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-014-0529-7

zbMATH Keywords

interactionsconsistencyGibbs samplerposterior probabilitybeta-prime priorgeneralized singular \(g\)-prior

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (5)

Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates ⋮ Multiple imputation and functional methods in the presence of measurement error and missingness in explanatory variables ⋮ Bayesian beta regression for bounded responses with unknown supports ⋮ Consistency of Bayes factor for nonnested model selection when the model dimension grows ⋮ A novel Bayesian approach for variable selection in linear regression models

Cites Work

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• Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models
• A study of variable selection using \(g\)-prior distribution with ridge parameter
• Fully Bayes factors with a generalized \(g\)-prior
• Structured variable selection and estimation
• Nonparametric regression using Bayesian variable selection
• Optimal predictive model selection.
• The risk inflation criterion for multiple regression
• Empirical Bayes vs. fully Bayes variable selection
• Calibration and empirical Bayes variable selection
• Bayes factor consistency for unbalanced ANOVA models
• Marginal Likelihood from the Gibbs Output
• A comment on D. V. Lindley's statistical paradox
• Mixtures of g Priors for Bayesian Variable Selection
• Estimating Optimal Transformations for Multiple Regression and Correlation
• Multivariate Bayesian Variable Selection and Prediction
• Bayesian Model Averaging for Linear Regression Models
• A Bayesian Variable-Selection Approach for Analyzing Designed Experiments with Complex Aliasing
• Bayes Factors
• Bayesian variable selection with related predictors
• Objective Bayesian Variable Selection
• Benchmark priors for Bayesian model averaging.

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