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BCa bootstrap (korigovan na pristrasnost i ubrzan)×Bejzijanski Bootstrap (Rubin)×Dvostruki (iterativni) ბootstrap×
OblastStatistikaStatistikaStatistika
PorodicaRegression modelRegression modelRegression model
Godina nastanka198719811986
TvoracBradley EfronRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TipResampling confidence intervalResampling / posterior simulationResampling calibration (nested bootstrap)
Temeljni izvorEfron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗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 ↗
Drugi naziviBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence intervalBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)
Srodne555
SažetakThe BCa bootstrap is a resampling method, introduced by Bradley Efron in 1987, that produces more accurate confidence intervals than the plain percentile bootstrap by applying a bias correction and an acceleration adjustment. It is recommended for skewed distributions and small samples.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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ScholarGateUporedite metode: BCa Bootstrap · Bayesian Bootstrap · Double Bootstrap. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare