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حوزهآمارآمار
خانوادهRegression modelRegression model
سال پیدایش19931981
پدیدآورEfron & Tibshirani; Davison & HinkleyRubin (1981); large-sample theory by Lo (1987)
نوعResampling-based inference (model-based)Resampling / posterior simulation
منبع بنیادینEfron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. CRC Press. ISBN: 978-0412042317Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI ↗
نام‌های دیگرparametrik bootstrap, model-based bootstrap, parametric resamplingBayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap
مرتبط55
خلاصهThe 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 Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated.
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ScholarGateمقایسهٔ روش‌ها: Parametric Bootstrap · Bayesian Bootstrap. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare