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Bejzijanski Bootstrap (Rubin)×Dvostruki (iterativni) ბootstrap×
OblastStatistikaStatistika
PorodicaRegression modelRegression model
Godina nastanka19811986
TvoracRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TipResampling / posterior simulationResampling calibration (nested bootstrap)
Temeljni izvorRubin, 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 ↗
Drugi naziviBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)
Srodne55
SažetakThe 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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ScholarGateUporedite metode: Bayesian Bootstrap · Double Bootstrap. Preuzeto 2026-06-16 sa https://scholargate.app/sr/compare