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| Corrélation Robuste (Spearman, Kendall et Biweight)× | Corrélation de rang de Tau de Kendall× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille≠ | Regression model | Hypothesis test |
| Année d'origine≠ | 2012 | 1938 |
| Auteur d'origine≠ | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition | Maurice G. Kendall |
| Type≠ | Robust correlation measures | Rank-based association measure |
| Source fondatrice≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Academic Press. ISBN: 978-0123869838 | Kendall, M. G. (1938). A new measure of rank correlation. Biometrika, 30(1–2), 81–93. DOI ↗ |
| Alias≠ | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation | Kendall's tau, Kendall tau-b, tau correlation, Kendall Tau Korelasyonu |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | Robust Correlation is a family of association measures that resist outliers, covering Spearman's rank correlation, Kendall's tau, and the biweight midcorrelation. Drawing on the robust-statistics tradition described by Wilcox (2012) and Shevlyakov & Oja (2016), it measures how strongly two variables move together without being distorted by a few extreme points. | Kendall Tau is a nonparametric rank correlation coefficient introduced by Maurice G. Kendall in 1938 to measure the strength and direction of a monotone association between two ordinal or continuous variables. It is particularly suited to small samples and datasets containing many tied ranks, where the Spearman coefficient can be less stable. |
| ScholarGateJeu de données ↗ |
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