Modified ridge-type estimator for the gamma regression model

被引：19
|
作者：
Lukman, Adewale F. [1 ,2 ]
Ayinde, Kayode [3 ]
Kibria, B. M. Golam [4 ]
Adewuyi, Emmanuel T. [3 ]
机构：
[1] Landmark Univ, Dept Phys Sci, Omu Aran, Nigeria
[2] Inst Poincare, Ctr Emile Borel, Paris, France
[3] Fed Univ Technol Akure, Dept Stat, Akure, Nigeria
[4] Florida Int Univ, Dept Math & Stat, Miami, FL 33199 USA
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2022年 / 51卷 / 09期
关键词：
Gamma modified ridge-type; Gamma regression; Linear regression model; Modified ridge-type; PERFORMANCE;
D O I：
10.1080/03610918.2020.1752720
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 modified ridge-type estimator has been shown to cushion the effects of multicollinearity in the linear regression model. Recent studies have shown the adverse effects of multicollinearity in the gamma regression model (GRM). We proposed a gamma modified ridge-type estimator to tackle this problem. We derived the properties of this estimator and conducted a theoretical comparison with some of the existing estimators. A real-life example and simulation study show that the proposed estimator gains an advantage over other estimators in terms of the mean square error.
引用
收藏
页码：5009 / 5023
页数：15
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