Baranchick-type Estimators of a Multivariate Normal Mean Under the General Quadratic Loss Function

被引：1

作者：

Hamdaoui, Abdenour ^{[1
,2
]}

Benkhaled, Abdelkader ^{[3
]}

Terbeche, Mekki ^{[1
,4
]}

机构：

[1] Univ Sci & Technol Mohamed Boudiaf, Dept Math, Oran, Algeria

[2] Lab Stat & Random Modelisat LSMA, Tilimsen, Algeria

[3] Mascara Univ Mustapha Stambouli, Lab Geomat Ecol & Environm LGEO2E, Dept Biol, Mascara, Algeria

[4] USTO MB, Lab Anal & Applicat Radiat LAAR, Oran, Algeria

来源：

JOURNAL OF SIBERIAN FEDERAL UNIVERSITY-MATHEMATICS & PHYSICS | 2020年 / 13卷 / 05期

关键词：

covariance matrix; James-Stein estimator; loss function; multivariate gaussian random variable; non-central chi-square distribution; shrinkage estimator; MINIMAX ESTIMATORS; FAMILY;

D O I：

10.17516/1997-1397-2020-13-5-608-621

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The problem of estimating the mean of a multivariate normal distribution by different types of shrinkage estimators is investigated. We established the minimaxity of Baranchick-type estimators for identity covariance matrix and the matrix associated to the loss function is diagonal. In particular the class of James-Stein estimator is presented. The general situation for both matrices cited above is discussed.

引用

页码：608 / 621

页数：14

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