Robust Estimation in the Logistic Regression Model

  • Ana M. Bianco
  • Víctor J. Yohai
Part of the Lecture Notes in Statistics book series (LNS, volume 109)


A new class of robust and Fisher-consistent M-estimates for the logistic regression models is introduced. We show that these estimates are consistent and asymptotically normal. Their robustness is studied through the computation of asymptotic bias curves under point-mass contamination for the case when the covariates follow a multivariate normal distribution. We illustrate the behavior of these estimates with two data sets. Finally, we mention some possible extensions of these M-estimates for a multinomial response.

Key words and phrases

logistic regression model M-estimates robust estimates 

AMS 1991 subject classifications

Primary 62F35, 62J12 secondary 62F12 


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Copyright information

© Springer-Verlag New York, Inc. 1996

Authors and Affiliations

  • Ana M. Bianco
    • 1
  • Víctor J. Yohai
    • 2
    • 3
  1. 1.Universidad de Buenos AiresArgentina
  2. 2.Universidad de San AndrésArgentina
  3. 3.Universidad de Buenos AiresArgentina

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