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Multilevel Approximate Bayesian Computation×階層ベイズ推論×
分野ベイズベイズ
系統Bayesian methodsBayesian methods
提唱年2000s–2010s1980s–2000s
提唱者Extension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010sGelman, Hill, Raudenbush, Bryk
種類Simulation-based Bayesian inferenceBayesian hierarchical model
原典Beaumont, M. A., Zhang, W., & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. DOI ↗Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. ISBN: 978-0521686891
別名multilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsBayesian multilevel model, Bayesian hierarchical model, Bayesian mixed-effects model, Bayesian random-effects model
関連66
概要Multilevel Approximate Bayesian Computation (multilevel ABC) extends simulation-based Bayesian inference to hierarchically structured data. When the likelihood is intractable and observations are nested within groups, it replaces direct likelihood evaluation with simulations at each level of the hierarchy, accepting parameter draws whose simulated summary statistics are close to the observed ones.Multilevel Bayesian inference combines Bayesian probability with hierarchical data structures, treating group-level parameters as drawn from a common population distribution. It simultaneously estimates unit-level effects and the hyperparameters governing their variation, propagating full uncertainty through every level of the hierarchy via posterior sampling.
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ScholarGate手法を比較: Multilevel Approximate Bayesian Computation · Multilevel Bayesian Inference. 2026-06-17に以下より取得 https://scholargate.app/ja/compare