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Bootstrapinferens×Jackknife-resampling×
ÄmnesområdeStatistikStatistik
FamiljRegression modelRegression model
Ursprungsår19791956
UpphovspersonBradley EfronQuenouille (1956); reviewed by Miller (1974)
TypResampling-based inferenceResampling / bias and variance estimation
UrsprungskällaEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗
Aliasbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımıleave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme
Närliggande55
SammanfattningBootstrap 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.The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.
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ScholarGateJämför metoder: Bootstrap Inference · Jackknife. Hämtad 2026-06-17 från https://scholargate.app/sv/compare