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حوزهبیزیبیزی
خانوادهBayesian methodsBayesian methods
سال پیدایش1999 (BMA seminal); 2000s (missing-data extensions)1976–1987
پدیدآورHoeting, Madigan, Raftery, Volinsky (BMA); extended to missing data by Raftery, Madigan and othersRubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation)
نوعBayesian ensemble inference under incomplete dataBayesian probabilistic model
منبع بنیادینHoeting, J. A., Madigan, D., Raftery, A. E. & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382-417. link ↗Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860
نام‌های دیگرBMA with missing data, Bayesian model averaging under missingness, BMA-MI, model-averaged imputationBayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model
مرتبط66
خلاصهBayesian Model Averaging with missing data (BMA-MD) simultaneously addresses two sources of uncertainty: which model best describes the data, and what the unobserved values are. Rather than selecting a single imputed dataset and a single model, the approach averages predictions across the full space of candidate models and plausible completions of the missing values, propagating both sources of uncertainty into every estimate and prediction.Bayesian inference with missing data treats unobserved values as unknown parameters and integrates them out of the posterior distribution. Rather than deleting or ad hoc imputing incomplete records, the method jointly models observed and missing data under an explicit missing-data mechanism, producing fully calibrated posterior uncertainty that honestly reflects what the data cannot tell us.
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ScholarGateمقایسهٔ روش‌ها: Bayesian model averaging with missing data · Bayesian Inference with Missing Data. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare