Robustness versus Efficiency for Nonparametric Correlation Measures
AbstractNonparametric 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2008_002.
Length: 25 p.
Date of creation: 2008
Date of revision:
Publication status: Published by:
Asymptotic Variance; Correlation; Gross-Error Sensitivity; Infuence function; Kendall correlation; Robustness; Spearman correlation.;
Other versions of this item:
- Croux, Christophe & Dehon, Catherine, 2008. "Robustness versus efficiency for nonparametric correlation measures," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/164226, Katholieke Universiteit Leuven.
- Christophe Croux & Catherine Dehon, . "Robustness versus efficiency for nonparametric correlation measures," ULB Institutional Repository 2013/8472, ULB -- Universite Libre de Bruxelles.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Croux, Christophe & Dehon, C, 2002. "Analyse canonique basée sur des estimateurs robustes de la matrice de covariance," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/85735, Katholieke Universiteit Leuven.
- Daraio, Cinzia & Moed, Henk F., 2011. "Is Italian science declining?," Research Policy, Elsevier, vol. 40(10), pages 1380-1392.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Benoit Pauwels).
If references are entirely missing, you can add them using this form.