Improved estimation of parameter matrices in a one-sample and two-sample problems

被引：1
|
作者：
Leung, PL [1 ]
Ng, FY [1 ]
机构：
[1] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2001年 / 53卷 / 04期
关键词：
covariance matrix; orthogonally invariant estimator; decision-theoretic estimation; shrinkage estimator; harmonic mean; eigenvalues;
D O I：
10.1023/A:1014661221279
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this paper, the problems of estimating the covariance matrix in a Wishart distribution (refer as one-sample problem) and the scale matrix in a multivariate F distribution (which arise naturally from a two-sample setting) are considered. A new class of estimators which shrink the eigenvalues towards their harmonic mean is proposed. It is shown that the new estimator dominates the best linear estimator under two scale invariant loss functions.
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页码：769 / 780
页数：12
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