Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Подвійний (ітераційний) бутстреп× | Блоковий бутстреп (рухомий блок та стаціонарний)× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1986 | 1989 |
| Автор методу≠ | Hall (1986); Beran (1987) | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) |
| Тип≠ | Resampling calibration (nested bootstrap) | Resampling inference for dependent data |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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). |
| ScholarGateНабір даних ↗ |
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