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Bootstrap Bayesian (Rubin)×Bootstrap BCa (Pembetulan Bias dan Pecutan)×
BidangStatistikStatistik
KeluargaRegression modelRegression model
Tahun asal19811987
PengasasRubin (1981); large-sample theory by Lo (1987)Bradley Efron
JenisResampling / posterior simulationResampling confidence interval
Sumber perintisRubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗Efron, B. (1987). Better Bootstrap Confidence Intervals. Journal of the American Statistical Association, 82(397), 171-185. DOI ↗
AliasBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval
Berkaitan55
RingkasanThe 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 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.
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ScholarGateBandingkan kaedah: Bayesian Bootstrap · BCa Bootstrap. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare