Influence functions of the Spearman and Kendall correlation measures |
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Authors: | Christophe Croux Catherine Dehon |
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Affiliation: | 1. Faculty of Business and Economics, and K.U. Leuven, Naamsestraat 69, 3000, Leuven, Belgium 2. Tilburg University, Tilburg, The Netherlands 3. Université libre de Bruxelles, ECARES, and Institut de Recherche en Statistique, CP-114, Av. F.D. Roosevelt 50, 1050, Brussels, Belgium
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Abstract: | 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. |
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