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| Régression linéaire simple robuste× | Estimateur de Theil-Sen× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1964-1987 | 1968 |
| Auteur d'origine≠ | Peter J. Huber (M-estimators, 1964); Rousseeuw & Leroy (practical framework, 1987) | Henri Theil (1950); P. K. Sen (1968) |
| Type | Robust linear regression | Robust linear regression |
| Source fondatrice≠ | Rousseeuw, P. J., & Leroy, A. M. (1987). Robust Regression and Outlier Detection. John Wiley & Sons. ISBN: 978-0471852339 | Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389. DOI ↗ |
| Alias≠ | robust SLR, M-estimator simple regression, outlier-resistant simple regression, robust bivariate regression | Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator |
| Apparentées | 6 | 6 |
| Résumé≠ | Robust simple linear regression fits a straight line through bivariate data using loss functions or weighting schemes that down-weight outliers, producing slope and intercept estimates that are far less sensitive to extreme observations than ordinary least squares while remaining easy to interpret. | The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%. |
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