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| Bootstrap BCa (corretto per distorsione e accelerazione)× | Bootstrap Wild per l'Inferenza di Regressione× | |
|---|---|---|
| Campo | Statistica | Statistica |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1987 | 1986 |
| Ideatore≠ | Bradley Efron | Wu (1986); refined by Davidson & Flachaire (2008) |
| Tipo≠ | Resampling confidence interval | Resampling-based regression inference |
| Fonte seminale≠ | Efron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗ | Wu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI ↗ |
| Alias≠ | BCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval | wild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrap |
| Correlati | 5 | 5 |
| Sintesi≠ | 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 wild bootstrap is a resampling method for regression models with heteroscedastic errors, introduced by Wu (1986) and refined by Davidson and Flachaire (2008). It builds a bootstrap distribution by rescaling each fitted residual with a random sign, so that standard errors and confidence intervals stay valid when the error variance is not constant or the data are clustered. |
| ScholarGateInsieme di dati ↗ |
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