Two-stage shrunken least squares estimator and its superiority

被引：0

作者：

Song, Quanhong ^{[1
]}

Wang, Lichun ^{[1
]}

Wang, Liqun ^{[2
]}

机构：

[1] Beijing Jiaotong Univ, Dept Stat, Beijing 100044, Peoples R China

[2] Univ Manitoba, Dept Stat, Winnipeg, MB, Canada

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2024年 / 53卷 / 19期

关键词：

Two-stage estimator; generalized shrunken least squares estimator; multi-collinearity;

D O I：

10.1080/03610926.2023.2250487

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 linear regression model, the superiority of ordinary least squares estimator (OLSE) will be failed when there exist multi-collinearity problems. Based on the class of generalized shrunken least squares (GSLS) estimators suggested by Wang (1990), this article proposes a two-stage shrunken least squares estimator and discusses its superiority theoretically, and finally verifies the results by numerical simulations.

引用

页码：6717 / 6731

页数：15

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