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Bayesian Bootstrap (Rubin)×Doppelter (iterierter) Bootstrap×
FachgebietStatistikStatistik
FamilieRegression modelRegression model
Entstehungsjahr19811986
UrheberRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TypResampling / posterior simulationResampling calibration (nested bootstrap)
Wegweisende QuelleRubin, 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 ↗
AliasnamenBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)
Verwandt55
ZusammenfassungThe 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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ScholarGateMethoden vergleichen: Bayesian Bootstrap · Double Bootstrap. Abgerufen am 2026-06-16 von https://scholargate.app/de/compare