Shrinkage Estimation in Restricted Elliptical Regression Models

被引：3
|
作者：
Fallah, Reza [1 ]
Arashi, Mohammad [2 ]
Tabatabaey, Seyed Mohammad M. [1 ]
机构：
[1] Ferdowsi Univ Mashhad, Dept Stat, Int Campus, Mashhad, Iran
[2] Shahrood Univ Technol, Dept Stat, Shahrood, Iran
来源：
JIRSS-JOURNAL OF THE IRANIAN STATISTICAL SOCIETY | 2018年 / 17卷 / 01期
关键词：
Approximate risk; Elliptically contoured distribution; Linear regression model; Restricted estimator; Shrinkage estimator;
D O I：
10.29252/jirss.17.1.49
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 the restricted elliptical linear model, an approximation for the risk of a general shrinkage estimator of the regression vector-parameter is given. Superiority condition of the shrinkage estimator over the restricted estimator is investigated under the elliptical assumption. It is evident from numerical results that the shrinkage estimator performs better than the unrestricted one in the multivariate t-regression model.
引用
收藏
页码：49 / 61
页数：13
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