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January, 1976 Admissible Minimax Estimation of a Multivariate Normal Mean with Arbitrary Quadratic Loss
James O. Berger
Ann. Statist. 4(1): 223-226 (January, 1976). DOI: 10.1214/aos/1176343356

Abstract

The problem of estimating the mean of a $p$-variate $(p \geqq 3)$ normal distribution is considered. It is assumed that the covariance matrix $\not\sum$ is known and that the loss function is quadratic. A class of minimax estimators is given, out of which admissible minimax estimators are developed.

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James O. Berger. "Admissible Minimax Estimation of a Multivariate Normal Mean with Arbitrary Quadratic Loss." Ann. Statist. 4 (1) 223 - 226, January, 1976. https://doi.org/10.1214/aos/1176343356

Information

Published: January, 1976
First available in Project Euclid: 12 April 2007

zbMATH: 0322.62007
MathSciNet: MR397940
Digital Object Identifier: 10.1214/aos/1176343356

Subjects:
Primary: 62C15
Secondary: 62F10 , 62H99

Keywords: admissible , generalized Bayes , minimax , normal mean , quadratic loss

Rights: Copyright © 1976 Institute of Mathematical Statistics

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Vol.4 • No. 1 • January, 1976
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