Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Двойной (итерированный) бутстрэп× | Блочная бутстрэп-выборка (скользящий блок и стационарная)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1986 | 1989 |
| Автор метода≠ | Hall (1986); Beran (1987) | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) |
| Тип≠ | Resampling calibration (nested bootstrap) | Resampling inference for dependent data |
| Основополагающий источник≠ | Hall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗ | Künsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. Annals of Statistics, 17(3), 1217-1241. DOI ↗ |
| Другие названия≠ | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) |
| Связанные | 5 | 5 |
| Сводка≠ | The double bootstrap is a resampling method that calibrates a bootstrap confidence interval with a second, nested layer of bootstrap to bring its actual coverage closer to the nominal level. Introduced by Hall (1986) and Beran (1987), it is especially valuable for small samples and skewed distributions where a single-layer bootstrap under-covers. | 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). |
| ScholarGateНабор данных ↗ |
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