An Efficient Mallows-Type One-Step GM-Estimator in linear Models

  • Song, Moon-Sup (Department of Statistics, Seoul National University) ;
  • Park, Changsoon (Department of Applied Statistics, Chung-Ang University) ;
  • Nam, Ho-Soo (Department of Industrial Engineering, Dongseo University)
  • Published : 1998.09.01

Abstract

This paper deals with a robust regression estimator. We propose an efficient one-step GM-estimator, which has a bounded influence function and a high breakdown point. The main idea of this paper is to use the Mallows-type weights which depend on both the predictor variables and the residuals from a high breakdown initial estimator. The proposed weighting scheme severely downweights the bad leverage points and slightly downweights the good leverage points. Under some regularity conditions, we compute the finite-sample breakdown point and prove the asymptotic normality. Some simulation results and a numerical example are also presented.

Keywords

References

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