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분야통계학통계학
계열Regression modelRegression model
기원 연도19931986
창시자Efron & Tibshirani; Davison & HinkleyWu (1986); refined by Davidson & Flachaire (2008)
유형Resampling-based inference (model-based)Resampling-based regression inference
원전Efron, 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 ↗
별칭parametrik bootstrap, model-based bootstrap, parametric resamplingwild bootstrap, wild cluster bootstrap, Wu-Liu resampling, Wild Bootstrap
관련55
요약The 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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