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Robust inference for generalized linear models with application to logistic regression

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  • Adimari, Gianfranco
  • Ventura, Laura

Abstract

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

Suggested Citation

  • Adimari, Gianfranco & Ventura, Laura, 2001. "Robust inference for generalized linear models with application to logistic regression," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 413-419, December.
  • Handle: RePEc:eee:stapro:v:55:y:2001:i:4:p:413-419
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    1. repec:spr:stmapp:v:11:y:2002:i:2:d:10.1007_bf02511485 is not listed on IDEAS
    2. Daniel B. Hall & Jing Shen, 2010. "Robust Estimation for Zero-Inflated Poisson Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 237-252.

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