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W-估计量稳健回归(Welsch / Tukey Bisquare)×S估计量稳健回归×
领域统计学统计学
方法族Regression modelRegression model
起源年份19741984
提出者Beaton & Tukey (bisquare weight); Welsch (Welsch weight)Rousseeuw & Yohai (1984)
类型Robust regression (redescending M-estimator)Robust linear regression
开创性文献Beaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185. DOI ↗Rousseeuw, P. J. & Yohai, V. J. (1984). Robust Regression by Means of S-Estimators. In Robust and Nonlinear Time Series Analysis (Lecture Notes in Statistics, Vol. 26, pp. 256-272). Springer. DOI ↗
别名Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare)S-estimation, robust S-regression, S-Tahmin Edici
相关45
摘要The 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 S-estimator is a robust linear-regression method, introduced by Rousseeuw and Yohai in 1984, that estimates the coefficients by minimising a robust M-estimate of the residual scale rather than the variance of the residuals. By driving down a bounded measure of residual spread it can attain a breakdown point of up to 50%, so it stays reliable even when a large share of the data are outliers, and it provides the first stage of the well-known MM-estimator.
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ScholarGate方法对比: W-Estimator · S-Estimator. 于 2026-06-19 检索自 https://scholargate.app/zh/compare