ScholarGate
Asistent

Porovnať metódy

Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.

BCa Bootstrap (Bias-Corrected and Accelerated)×Bayesovský bootstrap (Rubin)×Dvojitý (iterovaný) bootstrap×
OdborŠtatistikaŠtatistikaŠtatistika
RodinaRegression modelRegression modelRegression model
Rok vzniku198719811986
TvorcaBradley EfronRubin (1981); large-sample theory by Lo (1987)Hall (1986); Beran (1987)
TypResampling confidence intervalResampling / posterior simulationResampling calibration (nested bootstrap)
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 ↗Hall, P. (1986). On the Bootstrap and Confidence Intervals. Annals of Statistics, 14(4), 1431-1452. DOI ↗
Ďalšie názvyBCa 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)
Príbuzné555
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.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.
ScholarGateDátová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Prejsť na hľadanie Stiahnuť snímky

ScholarGatePorovnať metódy: BCa Bootstrap · Bayesian Bootstrap · Double Bootstrap. Získané 2026-06-17 z https://scholargate.app/sk/compare