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Robustness versus Efficiency for Nonparametric Correlation Measures

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  • Christophe Croux
  • Catherine Dehon

Abstract

Nonparametric correlation measures at the Kendall and Spearman correlation are widely used in the behavioral sciences. These measures are often said to be robust, in the sense of being resistant to outlying observations. In this note we formally study their robustness by means of their infuence functions. Since robustness of an estimator often comes at the price of a loss in precision, we compute effciencies at the normal model. A comparison with robust correlation measures derived from robust covariance matrices is made. We conclude that both Spearman and Kendall correlation measures combine good robustness properties with high effciency.

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File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/54070/1/RePEc_eca_wpaper_2008_002.pdf
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Bibliographic Info

Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2008_002.

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Length: 25 p.
Date of creation: 2008
Date of revision:
Publication status: Published by:
Handle: RePEc:eca:wpaper:2008_002

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Keywords: Asymptotic Variance; Correlation; Gross-Error Sensitivity; Infuence function; Kendall correlation; Robustness; Spearman correlation.;

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Cited by:
  1. Daraio, Cinzia & Moed, Henk F., 2011. "Is Italian science declining?," Research Policy, Elsevier, vol. 40(10), pages 1380-1392.

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