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Regressão Robusta W-Estimator (Welsch / Tukey Bisquare)×Estimador de Theil-Sen×
ÁreaEstatísticaEstatística
FamíliaRegression modelRegression model
Ano de origem19741968
Autor originalBeaton & Tukey (bisquare weight); Welsch (Welsch weight)Henri Theil (1950); P. K. Sen (1968)
TipoRobust regression (redescending M-estimator)Robust linear regression
Fonte seminalBeaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185. 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 ↗
Outros nomesTukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare)Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
Relacionados46
ResumoThe W-estimator is a family of robust M-estimator variants for linear regression that use the Tukey bisquare and Welsch weight functions, introduced in the line of work going back to Beaton and Tukey (1974). Because its weights fall rapidly toward zero as a residual grows, it resists outliers more strongly than the Huber M-estimator.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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ScholarGateComparar métodos: W-Estimator · Theil-Sen Estimator. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare