A new Liu-type estimator

被引：18
|
作者：
Kurnaz, Fatma Sevinc [1 ]
Akay, Kadri Ulas [2 ]
机构：
[1] Yildiz Tekn Univ, Dept Stat, Istanbul, Turkey
[2] Istanbul Univ, Dept Math, TR-34134 Istanbul, Turkey
来源：
STATISTICAL PAPERS | 2015年 / 56卷 / 02期
关键词：
Biased regression; Mean squared error; Multicollinearity; Ridge regression; Liu estimator; MEAN-SQUARE ERROR; RIDGE REGRESSION; LINEAR-REGRESSION;
D O I：
10.1007/s00362-014-0594-6
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：
The purpose of this paper is to introduce a new general Liu-type estimator which includes the ordinary least squares (OLS), ordinary ridge regression (ORR), Liu estimators and some estimators with two biasing parameters as special cases. Also, we investigate the superiority of the new Liu-type estimator to the OLS, ORR, Liu estimators and the estimators with two biasing parameters under the matrix mean squared error (MMSE) criterion. Furthermore, the results are illustrated both theoretically and graphically on the Portland cement dataset which is widely used in literature.
引用
收藏
页码：495 / 517
页数：23
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