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
收藏
页码：325 / 336
页数：12
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