EFFICIENCY OF THE PRINCIPAL COMPONENT LIU-TYPE ESTIMATOR IN LOGISTIC REGRESSION

被引：0

作者：

Wu, Jibo ^{[1
]}

Asar, Yasin ^{[2
]}

机构：

[1] Chongqing Univ Arts & Sci, Sch Math & Finance, Chongqing, Peoples R China

[2] Necmettin Erbakan Univ, Dept Math Comp Sci, TR-42090 Konya, Turkey

来源：

REVSTAT-STATISTICAL JOURNAL | 2020年 / 18卷 / 03期

关键词：

Liu-type estimator; logistic regression; mean squared error matrix; maximum likelihood estimator; multicollinearity; RIDGE-REGRESSION;

D O I：

暂无

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 we propose a principal component Liu-type logistic estimator by combining the principal component logistic regression estimator and Liu-type logistic estimator to overcome the multicollinearity problem. The superiority of the new estimator over some related estimators are studied under the asymptotic mean squared error matrix. A Monte Carlo simulation experiment is designed to compare the performances of the estimators using mean squared error criterion. Finally, a conclusion section is presented.

引用

页码：325 / 336

页数：12

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