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Multilevel Approximate Bayesian Computation×欠損値を有するベイズ階層モデル×
分野ベイズベイズ
系統Bayesian methodsBayesian methods
提唱年2000s–2010s1990s–2000s
提唱者Extension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010sGelman, Rubin, Little (and collaborators)
種類Simulation-based Bayesian inferenceBayesian hierarchical model with missing-data integration
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., 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
別名multilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsBHM missing data, multilevel Bayesian missing data model, hierarchical Bayesian imputation, Bayesian multilevel model with incomplete data
関連65
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.A Bayesian hierarchical model with missing data treats unobserved values as additional unknowns and samples them jointly with all model parameters from the posterior. The nested structure of the hierarchy borrows strength across groups, while the Bayesian framework naturally propagates uncertainty from missingness through every estimate and prediction.
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ScholarGate手法を比較: Multilevel Approximate Bayesian Computation · Bayesian Hierarchical Model with Missing Data. 2026-06-17に以下より取得 https://scholargate.app/ja/compare