The Annals of Statistics

Admissible Minimax Estimation of a Multivariate Normal Mean with Arbitrary Quadratic Loss

James O. Berger

Full-text: Open access

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.

Article information

Source
Ann. Statist., Volume 4, Number 1 (1976), 223-226.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176343356

Digital Object Identifier
doi:10.1214/aos/1176343356

Mathematical Reviews number (MathSciNet)
MR397940

Zentralblatt MATH identifier
0322.62007

JSTOR
links.jstor.org

Subjects
Primary: 62C15: Admissibility
Secondary: 62F10: Point estimation 62H99: None of the above, but in this section

Keywords
Admissible minimax normal mean generalized Bayes quadratic loss

Citation

Berger, James O. Admissible Minimax Estimation of a Multivariate Normal Mean with Arbitrary Quadratic Loss. Ann. Statist. 4 (1976), no. 1, 223--226. doi:10.1214/aos/1176343356. https://projecteuclid.org/euclid.aos/1176343356


Export citation