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Bootstrap BCa (corrigé du biais et accéléré)×Le Bootstrap Bayésien (Rubin)×Bootstrap itéré×
DomaineStatistiqueStatistiqueStatistique
FamilleRegression modelRegression modelRegression model
Année d'origine198719811986
Auteur d'origineBradley EfronRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TypeResampling confidence intervalResampling / posterior simulationResampling calibration (nested bootstrap)
Source fondatriceEfron, 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 ↗
AliasBCa 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)
Apparentées555
RésuméThe 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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ScholarGateComparer des méthodes: BCa Bootstrap · Bayesian Bootstrap · Double Bootstrap. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare