Robust Estimators for Poisson Regression

作     者：Idriss Abdelmajid Idriss Weihu Cheng Idriss Abdelmajid Idriss;Weihu Cheng

作者机构：College of Applied Science Department of Statistics Beijing University of Technology Beijing China 

出 版 物：《Open Journal of Statistics》 (统计学期刊（英文）)

年 卷 期：2023年第13卷第1期

页      面：112-118页

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

主　　题：Poisson Regression Model Maximum Likelihood Estimator Robust Estimation Contaminated Model Weighted Maximum Likelihood Estimator 

摘      要：The present paper proposes a new robust estimator for Poisson regression models. We used the weighted maximum likelihood estimators which are regarded as Mallows-type estimators. We perform a Monte Carlo simulation study to assess the performance of a suggested estimator compared to the maximum likelihood estimator and some robust methods. The result shows that, in general, all robust methods in this paper perform better than the classical maximum likelihood estimators when the model contains outliers. The proposed estimators showed the best performance compared to other robust estimators.