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حوزهآمارآمار
خانوادهRegression modelRegression model
سال پیدایش19891956
پدیدآورKünsch (moving block, 1989); Politis & Romano (stationary, 1994)Quenouille (1956); reviewed by Miller (1974)
نوعResampling inference for dependent dataResampling / bias and variance estimation
منبع بنیادینKünsch, H. R. (1989). The Jackknife and the Bootstrap for General Stationary Observations. Annals of Statistics, 17(3), 1217-1241. DOI ↗Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗
نام‌های دیگرmoving block bootstrap, stationary bootstrap, blok bootstrap (moving block / stationary)leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme
مرتبط55
خلاصهBlock bootstrap is a resampling method for dependent, autocorrelated time-series data: instead of resampling single observations, it resamples whole blocks of consecutive observations so the serial-correlation structure is preserved. The moving block variant was introduced by Künsch (1989) and the stationary variant by Politis and Romano (1994).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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ScholarGateمقایسهٔ روش‌ها: Block Bootstrap · Jackknife. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare