Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Tau (τ) regresijas novērtētājs× | Teila-Senas novērtētājs× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1988 | 1968 |
| Autors≠ | Yohai & Zamar | Henri Theil (1950); P. K. Sen (1968) |
| Tips | Robust linear regression | Robust linear regression |
| Pirmavots≠ | Yohai, V. J., & Zamar, R. H. (1988). High Breakdown-Point Estimates of Regression by Means of the Minimization of an Efficient Scale. Journal of the American Statistical Association, 83(402), 406-413. 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 ↗ |
| Citi nosaukumi≠ | tau regression estimator, robust tau regression, Tau-Tahmin Edici | Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | The Tau estimator is a robust linear regression method introduced by Yohai and Zamar in 1988 that fits the model by minimising an efficient τ-scale of the residuals. It builds on the scale estimate of the S-estimator to combine a high breakdown point with high statistical efficiency, and is often used as an alternative to the MM-estimator in small samples. | 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%. |
| ScholarGateDatu kopa ↗ |
|
|