Porovnať metódy
Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Robustné vážené najmenšie štvorce (Robustné WLS)× | Regresia metódou najmenších štvorcov (OLS)× | |
|---|---|---|
| Odbor | Ekonometria | Ekonometria |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1964/1981 | 2019 |
| Tvorca≠ | Huber, P. J. | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Robust weighted regression | Linear regression |
| Pôvodný zdroj≠ | 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 |
| Ďalšie názvy | robust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regression | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Príbuzné | 5 | 5 |
| Zhrnutie≠ | 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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