Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Подвійний (ітераційний) бутстреп× | Бутстреп-інференс× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1986 | 1979 |
| Автор методу≠ | Hall (1986); Beran (1987) | Bradley Efron |
| Тип≠ | Resampling calibration (nested bootstrap) | Resampling-based inference |
| Основоположне джерело≠ | Hall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ |
| Інші назви | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı |
| 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. | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. |
| ScholarGateНабір даних ↗ |
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