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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Parametrische bootstrap×Bayesian Bootstrap×BCa Bootstrap (Bias-Corrected and Accelerated)×
VakgebiedStatistiekStatistiekStatistiek
FamilieRegression modelRegression modelRegression model
Jaar van ontstaan199319811987
GrondleggerEfron & Tibshirani; Davison & HinkleyRubin (1981); large-sample theory by Lo (1987)Bradley Efron
TypeResampling-based inference (model-based)Resampling / posterior simulationResampling confidence interval
Oorspronkelijke bronEfron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317Rubin, 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 ↗
Aliassenparametrik bootstrap, model-based bootstrap, parametric resamplingBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrapBCa Bootstrap (Bias-Corrected Accelerated), bias-corrected accelerated bootstrap, BCa confidence interval
Verwant555
SamenvattingThe parametric bootstrap is a resampling method that estimates standard errors and confidence intervals by drawing repeated samples from a parametric model that has been fitted to the data. Developed in the bootstrap literature of Efron and Tibshirani (1993) and Davison and Hinkley (1997), it replaces analytic derivations for non-normal distributions and complex statistics.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 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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ScholarGateMethoden vergelijken: Parametric Bootstrap · Bayesian Bootstrap · BCa Bootstrap. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare