Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Breakdown Point Analysis× | Heteroscedasticiteit-Robuuste (HC) Standaardfouten× | |
|---|---|---|
| Vakgebied | Statistiek | Statistiek |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1983 | 1980 |
| Grondlegger≠ | Hampel (1971); Donoho & Huber (1983) | Eicker; Huber; White (1980); MacKinnon & White (1985) |
| Type≠ | Robustness diagnostic for estimators | Robust covariance estimator for linear regression |
| Oorspronkelijke bron≠ | Donoho, D. L. & Huber, P. J. (1983). The Notion of Breakdown Point. In A Festschrift for Erich L. Lehmann (pp. 157-184). Wadsworth. link ↗ | White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817-838. DOI ↗ |
| Aliassen≠ | breakdown point, finite-sample breakdown point, robustness breakdown analysis, Bozunma Noktası Analizi | robust standard errors, White standard errors, Huber-Eicker-White standard errors, sandwich standard errors |
| Verwant | 5 | 5 |
| Samenvatting≠ | Breakdown point analysis quantifies the fraction of outliers an estimator can tolerate before it produces meaningless results. Formalised by Hampel (1971) and Donoho and Huber (1983), it is the standard tool for comparing the robustness of competing estimators. | Heteroscedasticity-robust standard errors are a correction to the covariance matrix of an OLS regression that yields valid inference when the error variance is not constant. Introduced by Halbert White in 1980 and refined into the finite-sample variants HC1-HC4 by MacKinnon and White in 1985, they leave the coefficient estimates unchanged but rebuild the standard errors so that t and F tests remain trustworthy under heteroscedasticity. |
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