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| Kvantilis regresszió× | Tau (τ) regressziós becslő× | |
|---|---|---|
| Tudományterület≠ | Ökonometria | Statisztika |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 1978 | 1988 |
| Megalkotó≠ | Koenker & Bassett | Yohai & Zamar |
| Típus≠ | Conditional quantile regression | Robust linear regression |
| Alapmű≠ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ | Yohai, V. J., & Zamar, R. H. (1988). High Breakdown-Point Estimates of Regression by Means of the Minimization of an Efficient Scale. Journal of the American Statistical Association, 83(402), 406-413. DOI ↗ |
| Alternatív nevek | conditional quantile regression, regression quantiles, Kantil Regresyon | tau regression estimator, robust tau regression, Tau-Tahmin Edici |
| Kapcsolódó≠ | 5 | 4 |
| Összefoglaló≠ | 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. | The Tau estimator is a robust linear regression method introduced by Yohai and Zamar in 1988 that fits the model by minimising an efficient τ-scale of the residuals. It builds on the scale estimate of the S-estimator to combine a high breakdown point with high statistical efficiency, and is often used as an alternative to the MM-estimator in small samples. |
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