Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Usanifu wa urejeshaji thabiti wa W-Estimator (Welsch / Tukey Bisquare)× | Mbinu ya S-estimator kwa ajili ya Regresi Imara× | |
|---|---|---|
| Nyanja | Takwimu | Takwimu |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1974 | 1984 |
| Mwanzilishi≠ | Beaton & Tukey (bisquare weight); Welsch (Welsch weight) | Rousseeuw & Yohai (1984) |
| Aina≠ | Robust regression (redescending M-estimator) | Robust linear regression |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala≠ | Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare) | S-estimation, robust S-regression, S-Tahmin Edici |
| Zinazohusiana≠ | 4 | 5 |
| Muhtasari≠ | 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. |
| ScholarGateSeti ya data ↗ |
|
|