Superiority of empirical Bayes estimation of error variance in linear model

被引：2
|
作者：
Chen, Ling [1 ,2 ]
Wei, Laisheng [1 ]
机构：
[1] Univ Sci & Technol China, Dept Stat & Finance, Hefei 230026, Peoples R China
[2] Anhui Univ, Sch Math Sci, Hefei 230039, Peoples R China
来源：
FRONTIERS OF MATHEMATICS IN CHINA | 2012年 / 7卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Linear regression model; error variance; parametric empirical Bayes estimation; mean square error criterion; simulation result; REGRESSION MODEL;
D O I：
10.1007/s11464-012-0198-1
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
In this paper, the Bayes estimator of the error variance is derived in a linear regression model, and the parametric empirical Bayes estimator (PEBE) is constructed. The superiority of the PEBE over the least squares estimator (LSE) is investigated under the mean square error (MSE) criterion. Finally, some simulation results for the PEBE are obtained.
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页码：629 / 644
页数：16
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