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Robustness against unexpected dependence in the location model

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  • Zamar, Ruben H.

Abstract

Robustness of M-estimates of location against unexpected dependence in the data is studied via a min--max asymptotic variance approach. A measure of dependence is defined and used to construct a neighborhood of the classical location model which includes dependent observations. The solution of the min--max problem is a Huber's type M-estimate with psi-function [psi]c. The tuning constant c tends to zero, i.e. [psi]c(x) --> sign(x) (the sample median score function), when the maximum degree of dependence allowed in the neighborhood increases. Thus the median, which is the most bias-robust estimate of location, is also approximately the most variance-robust in the present context.

Suggested Citation

  • Zamar, Ruben H., 1990. "Robustness against unexpected dependence in the location model," Statistics & Probability Letters, Elsevier, vol. 9(4), pages 367-374, April.
  • Handle: RePEc:eee:stapro:v:9:y:1990:i:4:p:367-374
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    Keywords

    Robustness M-estimates dependence;

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