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תחוםבייסיאניסימולציה
משפחהBayesian methodsProcess / pipeline
שנת המקור1991-20002002
הוגה השיטהFabio Cozman (credal networks); Peter Walley (imprecise probabilities)
סוגprobabilistic graphical model with set-valued probabilitiesSimulation-based Bayesian inference
מקור מכונןCozman, F. G. (2000). Credal networks. Artificial Intelligence, 120(2), 199-233. DOI ↗Beaumont, M.A., Zhang, W. & Balding, D.J. (2002). Approximate Bayesian Computation in Population Genetics. Genetics, 162(4), 2025-2035. DOI ↗
כינוייםRBN, credal network, imprecise Bayesian network, sensitivity analysis in Bayesian networksABC, likelihood-free inference, simulation-based inference, Yaklaşık Bayesçi Hesaplama (ABC)
קשורות55
תקצירA Robust Bayesian Network extends a classical Bayesian network by replacing each precise conditional probability table with a set of allowable probability distributions — called a credal set. Instead of a single probability for each query, inference returns a range of probabilities, honestly reflecting uncertainty about the model's numeric parameters while preserving the interpretable directed-acyclic-graph structure.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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ScholarGateהשוואת שיטות: Robust Bayesian Network · Approximate Bayesian Computation. אוחזר בתאריך 2026-06-15 מתוך https://scholargate.app/he/compare