Singular value shrinkage priors for Bayesian prediction

DOI10.1093/BIOMET/ASV036zbMath1419.62148arXiv1408.2951OpenAlexW1587416047MaRDI QIDQ3459439

Takeru Matsuda, Fumiyasu Komaki

Publication date: 8 January 2016

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1408.2951

zbMATH Keywords

shrinkage estimatorBayesian predictionmultivariate linear regressionmatrix-variate normal distributionStein's prior

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Bayesian inference (62F15)

Related Items (9)

On minimax optimality of sparse Bayes predictive density estimates ⋮ Ridge-type linear shrinkage estimation of the mean matrix of a high-dimensional normal distribution ⋮ Empirical Bayes matrix completion ⋮ Generalized Bayes estimators with closed forms for the normal mean and covariance matrices ⋮ Density prediction and the Stein phenomenon ⋮ Unnamed Item ⋮ Improved loss estimation for a normal mean matrix ⋮ Proper Bayes and minimax predictive densities related to estimation of a normal mean matrix ⋮ Minimax predictive density for sparse count data

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