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المجالالإحصاءالإحصاء
العائلةRegression modelRegression model
سنة النشأة19561979
صاحب الطريقةQuenouille (1956); reviewed by Miller (1974)Bradley Efron
النوعResampling / bias and variance estimationResampling-based inference
المصدر التأسيسيQuenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗
الأسماء البديلةleave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örneklemebootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı
ذات صلة55
الملخصThe 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.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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ScholarGateقارن الطرق: Jackknife · Bootstrap Inference. استُرجع بتاريخ 2026-06-15 من https://scholargate.app/ar/compare