Bayesian variable selection regression of multivariate responses for group data
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Publication:1699706
DOI10.1214/17-BA1081zbMath1384.62259OpenAlexW2765335234WikidataQ105876943 ScholiaQ105876943MaRDI QIDQ1699706
Anthony N. Pettitt, Bernoît Liquet, Matthew William Sutton, Kerrie L. Mengersen
Publication date: 23 February 2018
Published in: Bayesian Analysis (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.ba/1508983455
Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10)
Related Items (14)
Summaries of three keynote lectures at the SAE – 2018 ⋮ Bayesian group selection with non-local priors ⋮ Objective Bayesian group variable selection for linear model ⋮ High-dimensional multivariate posterior consistency under global-local shrinkage priors ⋮ Bayesian linear regression for multivariate responses under group sparsity ⋮ Penalized partial least square applied to structured data ⋮ A Bayesian approach for partial Gaussian graphical models with sparsity ⋮ The EAS approach to variable selection for multivariate response data in high-dimensional settings ⋮ A Bayesian group selection with compositional responses for analysis of radiologic tumor proportions and their genomic determinants ⋮ Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models ⋮ Consistent group selection with Bayesian high dimensional modeling ⋮ Feature screening for multi-response varying coefficient models with ultrahigh dimensional predictors ⋮ Ultra high-dimensional multivariate posterior contraction rate under shrinkage priors ⋮ Multivariate sparse Laplacian shrinkage for joint estimation of two graphical structures
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