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Robust inference for generalized linear models with application to logistic regression

✍ Scribed by Gianfranco Adimari; Laura Ventura

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
125 KB
Volume
55
Category
Article
ISSN
0167-7152

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✦ Synopsis

In this paper we consider a suitable scale adjustment of the estimating function which deΓΏnes a class of robust M-estimators for generalized linear models. This leads to a robust version of the quasi-proΓΏle 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.

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