Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Robustne kaalutud vähimruutude meetod (Robust WLS)× | Tavaline vähimruutude (OLS) regressioon× | |
|---|---|---|
| Valdkond | Ökonomeetria | Ökonomeetria |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 1964/1981 | 2019 |
| Looja≠ | Huber, P. J. | Wooldridge (textbook treatment); classical least squares |
| Tüüp≠ | Robust weighted regression | Linear regression |
| Algallikas≠ | Huber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Rööpnimetused | robust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regression | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Seotud | 5 | 5 |
| Kokkuvõte≠ | Robust WLS combines weighted least squares — which corrects for known or estimated heteroscedasticity — with robust M-estimation that down-weights influential outliers. The result is a regression estimator that is simultaneously efficient under non-constant error variance and resistant to observations that would otherwise distort coefficient estimates. | 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). |
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