Bayes minimax estimators of a multivariate normal mean, with application to generalized ridge regression

DOI10.1080/03610928308828645zbMath0533.62047OpenAlexW2095456167MaRDI QIDQ3316397

Pi-Erh Lin, Edward A. Cooley

Publication date: 1983

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928308828645

zbMATH Keywords

admissibilityrisk functionmultivariate normal meangeneralized Bayesgeneralized ridge regressioncanonical form of multiple regression

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian inference (62F15) Minimax procedures in statistical decision theory (62C20)

Cites Work

• Minimax estimation of a normal mean vector when the covariance matrix is unknown
• Estimation of the mean of a multivariate normal distribution
• Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
• Combining independent normal mean estimation problems with unknown variances
• Proper Bayes minimax estimators of the multivariate normal mean vector for the case of common unknown variances
• Generalized Bayes minimax estimators of the multivariate normal mean with unknown covariance matrix
• Proper Bayes Minimax Estimators of the Multivariate Normal Mean

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