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Divoký bootstrap pre regresnú inferenciu×Test permutáciou (randomizačný test)×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku19862005
TvorcaWu (1986); refined by Davidson & Flachaire (2008)Good (2005); Edgington & Onghena (2007); resampling tradition
TypResampling-based regression inferenceNonparametric resampling test
Pôvodný zdrojWu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI ↗Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792
Ďalšie názvywild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstraprandomization test, exact permutation test, re-randomization test, Permütasyon Testi
Príbuzné55
ZhrnutieThe 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.The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.
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ScholarGatePorovnať metódy: Wild Bootstrap · Permutation Test. Získané 2026-06-15 z https://scholargate.app/sk/compare