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Itereret bootstrap×Bayesian Bootstrap (Rubin)×
FagområdeStatistikStatistik
FamilieRegression modelRegression model
Oprindelsesår19861981
OphavspersonHall (1986); Beran (1987)Rubin (1981); large-sample theory by Lo (1987)
TypeResampling calibration (nested bootstrap)Resampling / posterior simulation
Oprindelig kildeHall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗
Aliasseriterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap
Relaterede55
ResuméThe 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.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.
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ScholarGateSammenlign metoder: Double Bootstrap · Bayesian Bootstrap. Hentet 2026-06-15 fra https://scholargate.app/da/compare