方法对比
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| 稳健分位数回归× | 分位数回归× | |
|---|---|---|
| 领域≠ | 统计学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1993–1997 | 1978 |
| 提出者≠ | Koenker & Bassett (1978); robust extensions by Machado (1993) and He (1997) | Koenker & Bassett |
| 类型≠ | Robust semiparametric regression | Conditional quantile regression |
| 开创性文献≠ | Koenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275 | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| 别名≠ | robust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQR | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 相关≠ | 6 | 5 |
| 摘要≠ | Robust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. |
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