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حوزهبیزیبیزی
خانوادهBayesian methodsBayesian methods
سال پیدایش1999–20121972 (Lindley & Smith); consolidated 1995–2013
پدیدآورHoeting, Madigan, Raftery, Volinsky (BMA); robustness extensions by Ley & Steel and othersLindley & Smith; Gelman et al.
نوعBayesian model selection and averagingBayesian multilevel model
منبع بنیادینHoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401. link ↗Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
نام‌های دیگرrobust BMA, outlier-robust BMA, robust model averaging, heavy-tailed BMAmultilevel Bayesian modeling, Bayesian hierarchical model, nested Bayesian model, partial pooling model
مرتبط66
خلاصهRobust Bayesian model averaging extends standard BMA by replacing sensitive conjugate priors with heavy-tailed or mixture priors (e.g., mixtures of g-priors), and optionally robust likelihoods, so that posterior model probabilities and averaged estimates remain stable when data contain outliers, influential observations, or when the prior on model parameters would otherwise dominate the results.Hierarchical Bayesian inference is a probabilistic modeling framework that organises parameters into levels, placing priors on the group-level parameters and hyperpriors on the parameters governing those priors. It enables partial pooling of information across groups, balancing the extremes of treating each group as independent or merging them into a single estimate.
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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Robust Bayesian Model Averaging · Hierarchical Bayesian Inference. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare