方法对比
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| 断点分析× | 异方差稳健 (HC) 标准误× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1983 | 1980 |
| 提出者≠ | Hampel (1971); Donoho & Huber (1983) | Eicker; Huber; White (1980); MacKinnon & White (1985) |
| 类型≠ | Robustness diagnostic for estimators | Robust covariance estimator for linear regression |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | 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 |
| 相关 | 5 | 5 |
| 摘要≠ | 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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