Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| BCa Bootstrap (Sesgado y Acelerado Corregido)× | Bootstrap Doble (Iterado)× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1987 | 1986 |
| Autor original≠ | Bradley Efron | Hall (1986); Beran (1987) |
| Tipo≠ | Resampling confidence interval | Resampling calibration (nested bootstrap) |
| Fuente seminal≠ | Efron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗ | Hall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗ |
| Alias≠ | BCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) |
| Relacionados | 5 | 5 |
| Resumen≠ | The BCa bootstrap is a resampling method, introduced by Bradley Efron in 1987, that produces more accurate confidence intervals than the plain percentile bootstrap by applying a bias correction and an acceleration adjustment. It is recommended for skewed distributions and small samples. | 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. |
| ScholarGateConjunto de datos ↗ |
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