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Bayesovský bootstrap (Rubin)×Dvojitý (iterovaný) bootstrap×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku19811986
TvorcaRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TypResampling / posterior simulationResampling calibration (nested bootstrap)
Pôvodný zdrojRubin, 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 ↗
Ďalšie názvyBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapiterated bootstrap, nested bootstrap, calibrated bootstrap, Çift Bootstrap (Double / Iterated Bootstrap)
Príbuzné55
ZhrnutieThe 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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ScholarGatePorovnať metódy: Bayesian Bootstrap · Double Bootstrap. Získané 2026-06-17 z https://scholargate.app/sk/compare