In this paper we consider a suitable scale adjustment of the estimating function which de.nes a class of robust M-estimators for generalized linear models. This leads to a robust version of the quasi-pro.le loglikelihood which allows us to derive robust likelihood ratio type tests for inference and model selection having the standard asymptotic behaviour. An application to logistic regression is discussed.
Robust inference for generalized linear models with application to logistic regression
ADIMARI, GIANFRANCO;VENTURA, LAURA
2001
Abstract
In this paper we consider a suitable scale adjustment of the estimating function which de.nes a class of robust M-estimators for generalized linear models. This leads to a robust version of the quasi-pro.le loglikelihood which allows us to derive robust likelihood ratio type tests for inference and model selection having the standard asymptotic behaviour. An application to logistic regression is discussed.File in questo prodotto:
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