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Višerazinska aproksimativna Bayesovska inferencija×Hijerarhijsko Bayesovo zaključivanje×
PodručjeBayesovska statistikaBayesovska statistika
ObiteljBayesian methodsBayesian methods
Godina nastanka2000s–2010s1972 (Lindley & Smith); consolidated 1995–2013
TvoracExtension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010sLindley & Smith; Gelman et al.
VrstaSimulation-based Bayesian inferenceBayesian multilevel model
Temeljni izvorBeaumont, 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
Drugi nazivimultilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsmultilevel Bayesian modeling, Bayesian hierarchical model, nested Bayesian model, partial pooling model
Srodne66
SažetakMultilevel 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.Hierarchical Bayesian inference is a probabilistic modeling framework that organises parameters into levels, placing priors on the group-level parameters and hyperpriors on the parameters governing those priors. It enables partial pooling of information across groups, balancing the extremes of treating each group as independent or merging them into a single estimate.
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ScholarGateUsporedite metode: Multilevel Approximate Bayesian Computation · Hierarchical Bayesian Inference. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare