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Multilevel Approximate Bayesian Computation×Approksimativ Bayesiansk Beregning×
FagfeltBayesianskSimulering
FamilieBayesian methodsProcess / pipeline
Opprinnelsesår2000s–2010s2002
OpphavspersonExtension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010s
TypeSimulation-based Bayesian inferenceSimulation-based Bayesian inference
Opprinnelig kildeBeaumont, 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 ↗
Aliasmultilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsABC, likelihood-free inference, simulation-based inference, Yaklaşık Bayesçi Hesaplama (ABC)
Relaterte65
SammendragMultilevel 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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ScholarGateSammenlign metoder: Multilevel Approximate Bayesian Computation · Approximate Bayesian Computation. Hentet 2026-06-15 fra https://scholargate.app/no/compare