Title: The Minimum Renyi's Pseudodistance Estimators for Generalized Linear Models
Abstract: Minimum Renyi's pseudodistance estimators have good robustness properties without a significant loss of efficiency for linear regression models. The main purpose of this chapter is to extend these minimum RP estimators to generalized linear models. This chapter derives asymptotic properties of the proposed estimators and examine the performance of the estimators in Poisson regression models through a simulation study, focusing on the robustness properties of the estimators. Epileptic seizure count is modeled using a Poisson regression model with three explanatory variables, namely, baseline seizure rate recorded over an eight week period prior to randomization. The proposed estimators are robust against data contamination, including outliers and leverage points, as well as consistent and asymptotically normal.
Publication Year: 2022
Publication Date: 2022-08-24
Language: en
Type: other
Indexed In: ['crossref']
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