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BCa Bootstrap (Bias-Corrected and Accelerated)×Bayesovský bootstrap (Rubin)×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku19871981
TvorcaBradley EfronRubin (1981); large-sample theory by Lo (1987)
TypResampling confidence intervalResampling / posterior simulation
Pôvodný zdrojEfron, 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 ↗
Ďalšie názvyBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence intervalBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap
Príbuzné55
ZhrnutieThe 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.
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ScholarGatePorovnať metódy: BCa Bootstrap · Bayesian Bootstrap. Získané 2026-06-15 z https://scholargate.app/sk/compare