MODIFIED RIDGE ESTIMATOR IN ZERO-INFLATED POISSON REGRESSION MODEL

被引：0

作者：

Younus, Farah Abdul Ghani ^{[1
]}

Othman, Rafal Adeeb ^{[1
]}

Algamal, Zakariya Yahya ^{[1
]}

机构：

[1] Univ Mosul, Dept Stat & Informat, Mosul, Iraq

来源：

INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES | 2022年 / 18卷

关键词：

Multicollinearity; Ridge estimator; Zero-inflated Poisson regression model; Monte Carlo simulation; NEGATIVE BINOMIAL REGRESSION; SELECTION; PARAMETER;

D O I：

暂无

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

The ridge estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The zero-inflated Poisson regression model (ZIPRM) is a well-known model in application when the response variable is a count data that has extra zeros. However, it is known that the variance of maximum likelihood estimator (MLE) of the ZIPRM coefficients can negatively be affected in the presence of multicollinearity. In this paper, a modification of ridge estimator is proposed to overcome the multicollinearity problem in the zero-inflated Poisson regression model. Our Monte Carlo simulation and real data application results suggest that the proposed estimator is better than the MLE estimator and ridge estimator in terms of MSE.

引用

页码：1245 / 1250

页数：6

共 35 条

[1] Almost unbiased ridge estimator in the count data regression models [J].