Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Regresioni Robust Vektori-Vlerë (Welsch / Tukey Bisquare)× | Regresioni me Mënyrën më të Vogël të Katrorëve (OLS)× | |
|---|---|---|
| Fusha≠ | Statistikë | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 1974 | 2019 |
| Krijuesi≠ | Beaton & Tukey (bisquare weight); Welsch (Welsch weight) | Wooldridge (textbook treatment); classical least squares |
| Lloji≠ | Robust regression (redescending M-estimator) | Linear regression |
| Burimi themelues≠ | 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 ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Emërtime të tjera | Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Të lidhura≠ | 4 | 5 |
| Përmbledhja≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateSeti i të dhënave ↗ |
|
|