Improved ridge estimators in a linear regression model

被引：9

作者：

Liu, Xu-Qing ^{[1
]}

Gao, Feng ^{[1
]}

Yu, Zhen-Feng ^{[1
]}

机构：

[1] Huaiyin Inst Technol, Fac Math & Phys, Huaian 223003, Peoples R China

来源：

JOURNAL OF APPLIED STATISTICS | 2013年 / 40卷 / 01期

关键词：

linear regression; improved ridge estimator; singular value decomposition; MSE; PRESS; NONORTHOGONAL PROBLEMS; PREDICTION; CRITERION; VARIABLES; ERROR;

D O I：

10.1080/02664763.2012.740623

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 notion of the improved ridge estimator (IRE) is put forward in the linear regression model y=X beta+e. The problem arises if augmenting the equation 0=c'a+e instead of 0=C a+? to the model. Three special IREs are considered and studied under the mean-squared error criterion and the prediction error sum of squares criterion. The simulations demonstrate that the proposed estimators are effective and recommendable, especially when multicollinearity is severe.

引用

页码：209 / 220

页数：12

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