Bayesian variable selection using an adaptive powered correlation prior

DOI10.1016/j.jspi.2008.12.004zbMath1162.62017OpenAlexW2081839634WikidataQ41829956 ScholiaQ41829956MaRDI QIDQ1022001

Howard D. Bondell, Arun Krishna, Sujit Kumar Ghosh

Publication date: 9 June 2009

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2772159

zbMATH Keywords

principal componentsBayesian variable selectioncollinearityZellner's \(g\)-priorpowered correlation prior

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Linear regression; mixed models (62J05) Bayesian inference (62F15) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (9)

Structured regularization for conditional Gaussian graphical models ⋮ Bayesian Variable Selection Under Collinearity ⋮ Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior ⋮ Bayesian Approaches to Shrinkage and Sparse Estimation ⋮ Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study ⋮ On consistency and optimality of Bayesian variable selection based on \(g\)-prior in normal linear regression models ⋮ Applications of Bayesian gene selection and classification with mixtures of generalized singular \(g\)-priors ⋮ Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression ⋮ Conjugate priors and variable selection for Bayesian quantile regression

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