方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 双重（迭代）自助法× | 块自举（移动块和固定块）× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1986 | 1989 |
| 提出者≠ | Hall (1986); Beran (1987) | Künsch (moving block, 1989); Politis & Romano (stationary, 1994) |
| 类型≠ | Resampling calibration (nested bootstrap) | Resampling inference for dependent data |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) | moving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary) |
| 相关 | 5 | 5 |
| 摘要≠ | 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). |
| ScholarGate数据集 ↗ |
|
|