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Bayesian Bootstrap (Rubin)×Dobbel (iterert) bootstrap×
FagfeltStatistikkStatistikk
FamilieRegression modelRegression model
Opprinnelsesår19811986
OpphavspersonRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TypeResampling / posterior simulationResampling calibration (nested bootstrap)
Opprinnelig kildeRubin, 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 ↗
AliasBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)
Relaterte55
SammendragThe 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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ScholarGateSammenlign metoder: Bayesian Bootstrap · Double Bootstrap. Hentet 2026-06-16 fra https://scholargate.app/no/compare