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Multilevel Approximate Bayesian Computation×尤度フリー推論のための近似ベイズ計算×
分野ベイズシミュレーション
系統Bayesian methodsProcess / pipeline
提唱年2000s–2010s2002
提唱者Extension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010s
種類Simulation-based Bayesian inferenceSimulation-based Bayesian inference
原典Beaumont, M. A., Zhang, W., & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. DOI ↗Beaumont, M.A., Zhang, W. & Balding, D.J. (2002). Approximate Bayesian Computation in Population Genetics. Genetics, 162(4), 2025-2035. DOI ↗
別名multilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsABC, likelihood-free inference, simulation-based inference, Yaklaşık Bayesçi Hesaplama (ABC)
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.Approximate Bayesian Computation (ABC) is a family of simulation-based inference methods that estimate posterior distributions without requiring an analytically tractable likelihood function. Introduced by Beaumont, Zhang and Balding (2002) in the context of population genetics, ABC replaced the intractable likelihood with repeated model simulation and a comparison of summary statistics between simulated and observed data.
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ScholarGate手法を比較: Multilevel Approximate Bayesian Computation · Approximate Bayesian Computation. 2026-06-15に以下より取得 https://scholargate.app/ja/compare