Influence functions of the Spearman and Kendall correlation measures

C. Croux, C. Dehon

Research output: Contribution to journalArticleScientificpeer-review

402 Citations (Scopus)


Nonparametric correlation estimators as the Kendall and Spearman correlation are widely used in the applied sciences. They are often said to be robust, in the sense of being resistant to outlying observations. In this paper we formally study their robustness by means of their influence functions and gross-error sensitivities. Since robustness of an estimator often comes at the price of an increased variance, we also compute statistical efficiencies at the normal model. We conclude that both the Spearman and Kendall correlation estimators combine a bounded and smooth influence function with a high efficiency. In a simulation experiment we compare these nonparametric estimators with correlations based on a robust covariance matrix estimator.
Original languageEnglish
Pages (from-to)497-515
JournalStatistical Methods and Applications
Issue number4
Publication statusPublished - 2010


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