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Bootstrap salvatge per a inferència en regressió×Inferencia Bootstrap×
CampEstadísticaEstadística
FamíliaRegression modelRegression model
Any d'origen19861979
Autor originalWu (1986); refined by Davidson & Flachaire (2008)Bradley Efron
TipusResampling-based regression inferenceResampling-based inference
Font seminalWu, 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 ↗
Àlieswild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrapbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Relacionats55
ResumThe 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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ScholarGateCompara mètodes: Wild Bootstrap · Bootstrap Inference. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare