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Wild Bootstrap til Regressionsinferens×Bootstrap-inferens×
FagområdeStatistikStatistik
FamilieRegression modelRegression model
Oprindelsesår19861979
OphavspersonWu (1986); refined by Davidson & Flachaire (2008)Bradley Efron
TypeResampling-based regression inferenceResampling-based inference
Oprindelig kildeWu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI ↗Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗
Aliasserwild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrapbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Relaterede55
ResuméThe wild bootstrap is a resampling method for regression models with heteroscedastic errors, introduced by Wu (1986) and refined by Davidson and Flachaire (2008). It builds a bootstrap distribution by rescaling each fitted residual with a random sign, so that standard errors and confidence intervals stay valid when the error variance is not constant or the data are clustered.Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.
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ScholarGateSammenlign metoder: Wild Bootstrap · Bootstrap Inference. Hentet 2026-06-15 fra https://scholargate.app/da/compare