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Bootstrap Parametrik×Wild Bootstrap untuk Inferensi Regresi×
BidangStatistikaStatistika
KeluargaRegression modelRegression model
Tahun asal19931986
PencetusEfron & Tibshirani; Davison & HinkleyWu (1986); refined by Davidson & Flachaire (2008)
TipeResampling-based inference (model-based)Resampling-based regression inference
Sumber perintisEfron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317Wu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI ↗
Aliasparametrik bootstrap, model-based bootstrap, parametric resamplingwild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrap
Terkait55
RingkasanThe 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 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.
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ScholarGateBandingkan metode: Parametric Bootstrap · Wild Bootstrap. Diakses 2026-06-15 dari https://scholargate.app/id/compare