Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Bootstrap Doble (Iterado)× | Bootstrap de Bloques (Bloque Móvil y Estacionario)× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1986 | 1989 |
| Autor original≠ | Hall (1986); Beran (1987) | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) |
| Tipo≠ | Resampling calibration (nested bootstrap) | Resampling inference for dependent data |
| Fuente seminal≠ | 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 ↗ |
| Alias≠ | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) |
| Relacionados | 5 | 5 |
| Resumen≠ | 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). |
| ScholarGateConjunto de datos ↗ |
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