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| Régression quantile (variantes non paramétriques)× | Estimateur de Theil-Sen× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1978 | 1968 |
| Auteur d'origine≠ | Koenker & Bassett | Henri Theil (1950); P. K. Sen (1968) |
| Type≠ | Quantile regression (nonparametric variants) | Robust linear regression |
| Source fondatrice≠ | Koenker, R. & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ | 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≠ | quantile regression, median regression, distribution-free quantile regression, Kantil Regresyon (Nonparametric Varyantlar) | Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator |
| Apparentées≠ | 5 | 6 |
| Résumé≠ | Quantile regression, introduced by Koenker and Bassett in 1978, models a chosen conditional quantile (such as the median or the 25th and 75th percentiles) of a continuous outcome rather than its mean. Its nonparametric variants fit these quantile relationships without assuming a distribution for the errors, making them a robust complement to mean-based regression on skewed data. | 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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