השוואת שיטות
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| אומד W - רגרסיה רובסטית (Welsch / Tukey Bisquare)× | MM-אמידה לרגרסיה רובסטית× | |
|---|---|---|
| תחום | סטטיסטיקה | סטטיסטיקה |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1974 | 1987 |
| הוגה השיטה≠ | Beaton & Tukey (bisquare weight); Welsch (Welsch weight) | Victor J. Yohai |
| סוג≠ | Robust regression (redescending M-estimator) | Robust linear regression |
| מקור מכונן≠ | 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 ↗ | Yohai, V. J. (1987). High Breakdown-Point and High Efficiency Robust Estimates for Regression. Annals of Statistics, 15(2), 642-656. DOI ↗ |
| כינויים | Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare) | MM-estimation, MM robust regression, high-breakdown high-efficiency estimator, MM-Tahmin Edici |
| קשורות≠ | 4 | 5 |
| תקציר≠ | 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 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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