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On the maxbias curve of residual admissible robust regression estimates

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  • Berrendero Díaz, José Ramón
  • Zamar, Rubén

Abstract

The robustness properties of a regression estimate are throughly described by its maxbias curve. However, this function is difficult to compute, especially when the regressors are not elliptically distributed. In this paper, we propose a general method for computing maxbias curves, valid for a large number of robust regression estimates, namely, those estimates defined by residual admissible functionals. Our results are also useful to compute maxbias curves when the regressors are not elliptically distributed. \Ve provide several examples of application of the method which include S-, T-, and signed R-estimates. MM-estimates are also studied under a related, although slightly different, approach.

Suggested Citation

  • Berrendero Díaz, José Ramón & Zamar, Rubén, 1995. "On the maxbias curve of residual admissible robust regression estimates," DES - Working Papers. Statistics and Econometrics. WS 10349, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:10349
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    Cited by:

    1. Berrendero, José R. & Zamar, Ruben H., 1999. "Global robustness of location and dispersion estimates," Statistics & Probability Letters, Elsevier, vol. 44(1), pages 63-72, August.

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    Keywords

    Maxbias curve;

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