Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| BCa Бутстреп (скорректированный по смещению и ускоренный)× | Байесовский бутстрэп (Рубин)× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1987 | 1981 |
| Автор метода≠ | Bradley Efron | Rubin (1981); large-sample theory by Lo (1987) |
| Тип≠ | Resampling confidence interval | Resampling / posterior simulation |
| Основополагающий источник≠ | Efron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗ | Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗ |
| Другие названия | BCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval | Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap |
| Связанные | 5 | 5 |
| Сводка≠ | 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 Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated. |
| ScholarGateНабор данных ↗ |
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