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Asymptotic Robustness for Shrinking Contamination

  • Christine H. Müller
Part of the Lecture Notes in Statistics book series (LNS, volume 124)

Abstract

In this chapter we show that the robustness concept based on influence functions (see Section 3.2) is closely connected with a robustness concept based on shrinking neighbourhoods. In particular, the concepts coincide for estimators given by Frechet differentiable functionals as is shown in Section 5.1. But Section 5.1 also shows that for robustness concepts based on shrinking neighbourhoods also the larger class of asymptotically linear estimators can be used instead of the class of estimators which satisfy some differentiability condition. Therefore the robustness properties are given for asymptotically linear estimators. Especially, these properties are derived in Section 5.2 for estimating a linear aspect in a linear model, in Section 5.3 for estimating a nonlinear aspect in a linear model and in Section 5.4 for estimation in a nonlinear model.

Keywords

Score Function Variance Estimator Asymptotic Normality Influence Function Linear Estimator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • Christine H. Müller
    • 1
  1. 1.Fachbereich Mathematik und Informatik, WE1Freie Universität BerlinBerlinGermany

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