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Perhitungan Bayesian Aproksimasi Multitingkat×Perhitungan Bayesian Aproksimatif×
BidangBayesianSimulasi
KeluargaBayesian methodsProcess / pipeline
Tahun asal2000s–2010s2002
PencetusExtension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010s
TipeSimulation-based Bayesian inferenceSimulation-based Bayesian inference
Sumber perintisBeaumont, 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)
Terkait65
RingkasanMultilevel 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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ScholarGateBandingkan metode: Multilevel Approximate Bayesian Computation · Approximate Bayesian Computation. Diakses 2026-06-15 dari https://scholargate.app/id/compare