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مُقدِّر S للانحدار القوي (S-Estimator for Robust Regression)×تقدير MM للانحدار القوي×
المجالالإحصاءالإحصاء
العائلةRegression modelRegression model
سنة النشأة19841987
صاحب الطريقةRousseeuw & Yohai (1984)Victor J. Yohai
النوعRobust linear regressionRobust linear regression
المصدر التأسيسيRousseeuw, 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 ↗Yohai, V. J. (1987). High Breakdown-Point and High Efficiency Robust Estimates for Regression. Annals of Statistics, 15(2), 642-656. DOI ↗
الأسماء البديلةS-estimation, robust S-regression, S-Tahmin EdiciMM-estimation, MM robust regression, high-breakdown high-efficiency estimator, MM-Tahmin Edici
ذات صلة55
الملخصThe 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.The MM-estimator is a robust linear regression method introduced by Victor J. Yohai in 1987. It combines the high breakdown point of an S-estimator with the high efficiency of an M-estimator, so it resists outliers strongly while still using the data efficiently when errors are well-behaved.
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ScholarGateقارن الطرق: S-Estimator · MM-Estimator. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare