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Multiniveau Approksimativ Bayesiansk Beregning×Multiniveau Bayesiansk Inferens×
FagområdeBayesianskBayesiansk
FamilieBayesian methodsBayesian methods
Oprindelsesår2000s–2010s1980s–2000s
OphavspersonExtension of ABC (Beaumont et al., 2002) to multilevel/hierarchical settings; developed across multiple authors in the 2010sGelman, Hill, Raudenbush, Bryk
TypeSimulation-based Bayesian inferenceBayesian hierarchical model
Oprindelig kildeBeaumont, M. A., Zhang, W., & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. DOI ↗Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. ISBN: 978-0521686891
Aliassermultilevel ABC, hierarchical ABC, multi-level ABC, ABC for hierarchical modelsBayesian multilevel model, Bayesian hierarchical model, Bayesian mixed-effects model, Bayesian random-effects model
Relaterede66
ResuméMultilevel 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.Multilevel Bayesian inference combines Bayesian probability with hierarchical data structures, treating group-level parameters as drawn from a common population distribution. It simultaneously estimates unit-level effects and the hyperparameters governing their variation, propagating full uncertainty through every level of the hierarchy via posterior sampling.
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ScholarGateSammenlign metoder: Multilevel Approximate Bayesian Computation · Multilevel Bayesian Inference. Hentet 2026-06-15 fra https://scholargate.app/da/compare