Comparison of Some Estimators under the Pitman's Closeness Criterion in Linear Regression Model

被引:2
|
作者
Wu, Jibo [1 ,2 ]
机构
[1] Chongqing Univ Arts & Sci, Dept Math, Chongqing 402160, Peoples R China
[2] Chongqing Univ Arts & Sci, KLDAIP, Chongqing 402160, Peoples R China
基金
中国国家自然科学基金;
关键词
PRINCIPAL COMPONENT REGRESSION; UNBIASED RIDGE; PARAMETERS; NEARNESS;
D O I
10.1155/2014/654949
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Batah et al. (2009) combined the unbiased ridge estimator and principal components regression estimator and introduced the modified r-k class estimator. They also showed that the modified r-k class estimator is superior to the ordinary least squares estimator and principal components regression estimator in the mean squared error matrix. In this paper, firstly, we will give a new method to obtain the modified r-k class estimator; secondly, we will discuss its properties in some detail, comparing the modified r-k class estimator to the ordinary least squares estimator and principal components regression estimator under the Pitman closeness criterion. A numerical example and a simulation study are given to illustrate our findings.
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页数:6
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