Minimax hierarchical empirical Bayes estimation in multivariate regression

DOI10.1006/jmva.2000.1985zbMath0992.62006OpenAlexW2042019447MaRDI QIDQ1599240

Samuel D. Oman

Publication date: 19 September 2002

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.2000.1985

zbMATH Keywords

mean squared errorprior informationJames-Stein estimatesubspace shrinkage

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (3)

Empirical Bayes decision rule for classification on defective items in Weibull distribution ⋮ A Bayes Empirical Bayes Decision Rule for Classification ⋮ Bayes Empirical Bayes Classification of Components Using Masked Data

Cites Work

• On estimation of a matrix of normal means with unknown covariance matrix
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• Adaptive multivariate ridge regression
• Estimation of the inverse covariance matrix: Random mixtures of the inverse Wishart matrix and the identity
• Multivariate empirical Bayes and estimation of covariance matrices
• Deriving unbiased risk estimators of multinormal mean and regression coefficient estimators using zonal polynomials
• Shrinkage estimation in the two-way multivariate normal model
• Minimax estimators in the normal MANOVA model
• A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Improved Estimators for Coefficients in Linear Regression
• Empirical Bayes on vector observations: An extension of Stein's method
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