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| Estimation winsorisée× | Corrélation Robuste (Spearman, Kendall et Biweight)× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1960 | 2012 |
| Auteur d'origine≠ | Dixon (1960); robust estimation tradition (Wilcox) | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition |
| Type≠ | Robust location/scale estimator | Robust correlation measures |
| Source fondatrice≠ | Dixon, W. J. (1960). Simplified Estimation from Censored Normal Samples. Annals of Mathematical Statistics, 31(2), 385-391. DOI ↗ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Academic Press. ISBN: 978-0123869838 |
| Alias≠ | winsorization, winsorized mean, Winsorize Edilmiş Tahmin | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation |
| Apparentées | 5 | 5 |
| Résumé≠ | Winsorized estimation is a robust technique that reduces the influence of outliers by clamping the extreme percentiles of a distribution to a chosen threshold. Introduced by Dixon (1960) and developed in the robust-estimation tradition of Wilcox, it keeps every observation in the sample rather than discarding any. | 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. |
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