1
Master’s degree graduate, College of science, Yasuj university, Yasuj, Iran.
2
Department of mathematics, College of science, Yasuj university, Yasuj, Iran
Abstract
Many regression estimation methods are severely affected by outliers, and large errors occur in their estimates. In recent years, robust methods have been developed to solve this problem. The minimum divergence density power estimator is an estimation method based on the minimum distance between two density functions, which provides robust estimation in situations where the data contains a number of outliers. In this study, we present the robust minimum divergence density power estimator method for estimating the parameters of the Poisson regression model, which can produce robust estimators with minimal loss in efficiency. We will also examine the performance of the proposed estimators by providing a real example.
