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حوزهآمارآمار
خانوادهRegression modelRegression model
سال پیدایش19562019
پدیدآورQuenouille (1956); reviewed by Miller (1974)Maronna, Martin, Yohai & Salibián-Barrera (textbook treatment); robust estimation tradition
نوعResampling / bias and variance estimationRobust time series model (AR / MA / ARIMA)
منبع بنیادینQuenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. DOI ↗Maronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust Statistics: Theory and Methods (with R) (2nd ed.). Wiley. ISBN: 978-1119214687
نام‌های دیگرleave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örneklemerobust ARIMA, robust autoregressive model, outlier-resistant time series, Robust Zaman Serisi Analizi
مرتبط55
خلاصهThe 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.Robust Time Series Analysis fits autoregressive, moving-average, and ARIMA models to series that contain outliers or structural breaks, using M-estimation or MM-estimation instead of ordinary least squares so that a few anomalous observations do not distort the fit. It follows the robust statistics tradition consolidated in Maronna, Martin, Yohai and Salibián-Barrera (2019).
ScholarGateمجموعه‌داده
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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Jackknife · Robust Time Series Analysis. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare