Admissibility and minimaxity of Bayes estimators for a normal mean matrix

DOI10.1016/j.jmva.2008.02.012zbMath1151.62008OpenAlexW1970698532MaRDI QIDQ957309

Hisayuki Tsukuma

Publication date: 27 November 2008

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2008.02.012

zbMATH Keywords

singular value decompositionBayes estimationorder statisticshrinkage estimatorminimaxityinadmissibilityisotonic regressionadmissibilityquadratic losssimultaneous estimation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Bayesian problems; characterization of Bayes procedures (62C10) Minimax procedures in statistical decision theory (62C20) Admissibility in statistical decision theory (62C15)

Related Items

Bayes minimax estimation of the mean matrix of matrix-variate normal distribution under balanced loss function ⋮ Matrix linear minimax estimators in a general multivariate linear model under a balanced loss function ⋮ Hierarchical multilinear models for multiway data ⋮ Improved loss estimation for a normal mean matrix ⋮ Shrinkage priors for Bayesian estimation of the mean matrix in an elliptically contoured distribution ⋮ Proper Bayes and minimax predictive densities related to estimation of a normal mean matrix ⋮ Proper Bayes minimax estimators of the normal mean matrix with common unknown variances ⋮ Minimax Estimation of the Mean Matrix of the Matrix Variate Normal Distribution under the Divergence Loss Function ⋮ Generalized Bayes minimax estimation of the normal mean matrix with unknown covariance matrix

Cites Work

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