On the Stein phenomenon under divergence loss and an unknown variance-covariance matrix

DOI10.1016/J.JMVA.2009.03.008zbMath1175.62008OpenAlexW2004717902MaRDI QIDQ1036797

Malay Ghosh, Victor Mergel

Publication date: 13 November 2009

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2009.03.008

zbMATH Keywords

admissibilityBaranchik class

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Minimax procedures in statistical decision theory (62C20) Analysis of variance and covariance (ANOVA) (62J10) Admissibility in statistical decision theory (62C15)

Related Items (3)

Reference priors via \(\alpha \)-divergence for a certain non-regular model in the presence of a nuisance parameter ⋮ Minimax Estimation of the Mean Matrix of the Matrix Variate Normal Distribution under the Divergence Loss Function ⋮ Hierarchical empirical Bayes estimation of two sample means under divergence loss

Cites Work

• Estimation, prediction and the Stein phenomenon under divergence loss
• Differential geometry of curved exponential families. Curvatures and information loss
• Improved minimax predictive densities under Kullback-Leibler loss
• A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
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