Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Μπεϋζιανή Μπουτστραπ (Rubin)× | Διπλός (Επαναληπτικός) Bootstrap× | |
|---|---|---|
| Πεδίο | Στατιστική | Στατιστική |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 1981 | 1986 |
| Δημιουργός≠ | Rubin (1981); large-sample theory by Lo (1987) | Hall (1986); Beran (1987) |
| Τύπος≠ | Resampling / posterior simulation | Resampling calibration (nested bootstrap) |
| Θεμελιώδης πηγή≠ | Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗ | Hall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗ |
| Εναλλακτικές ονομασίες≠ | Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap | iterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap) |
| Συναφείς | 5 | 5 |
| Σύνοψη≠ | 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. | 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. |
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