Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Квантильна регресія× | Оцінювач Тау (τ) регресії× | |
|---|---|---|
| Галузь≠ | Економетрика | Статистика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1978 | 1988 |
| Автор методу≠ | Koenker & Bassett | Yohai & Zamar |
| Тип≠ | Conditional quantile regression | Robust linear regression |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | conditional quantile regression, regression quantiles, Kantil Regresyon | tau regression estimator, robust tau regression, Tau-Tahmin Edici |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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