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Divlji bootstrap za regresijsko zaključivanje×Uporišna inferencija×
PodručjeStatistikaStatistika
ObiteljRegression modelRegression model
Godina nastanka19861979
TvoracWu (1986); refined by Davidson & Flachaire (2008)Bradley Efron
VrstaResampling-based regression inferenceResampling-based inference
Temeljni izvorWu, 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 ↗
Drugi naziviwild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrapbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
Srodne55
SažetakThe 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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ScholarGateUsporedite metode: Wild Bootstrap · Bootstrap Inference. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare