Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Блочная бутстрэп-выборка (скользящий блок и стационарная)× | Квантильная регрессия× | |
|---|---|---|
| Область≠ | Статистика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1989 | 1978 |
| Автор метода≠ | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) | Koenker & Bassett |
| Тип≠ | Resampling inference for dependent data | Conditional quantile regression |
| Основополагающий источник≠ | Künsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. Annals of Statistics, 17(3), 1217-1241. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Другие названия | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Связанные | 5 | 5 |
| Сводка≠ | Block bootstrap is a resampling method for dependent, autocorrelated time-series data: instead of resampling single observations, it resamples whole blocks of consecutive observations so the serial-correlation structure is preserved. The moving block variant was introduced by Künsch (1989) and the stationary variant by Politis and Romano (1994). | 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. |
| ScholarGateНабор данных ↗ |
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