On Bayesian lasso variable selection and the specification of the shrinkage parameter

DOI10.1007/s11222-012-9316-xzbMath1322.62110OpenAlexW2007107436MaRDI QIDQ746286

Ioannis Ntzoufras, Anastasia Lykou

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-012-9316-x

zbMATH Keywords

Bayes factorsshrinkageMCMCPearson correlationpartial correlationbenchmark and threshold correlationsgamma hyperprior for \(\lambda\)

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Measures of association (correlation, canonical correlation, etc.) (62H20) Bayesian inference (62F15) Statistical ranking and selection procedures (62F07)

Related Items

Bayesian variable selection and estimation for group Lasso, Approximate Gibbs sampler for Bayesian Huberized lasso, Variable selection in linear-circular regression models, Bayesian approaches to variable selection in mixture models with application to disease clustering, Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data, A robust Bayesian analysis of variable selection under prior ignorance, An efficient Monte Carlo EM algorithm for Bayesian lasso, Scalable Bayesian Regression in High Dimensions With Multiple Data Sources

Uses Software

• R
• WinBUGS
• spikeSlabGAM
• Monomvn

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