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Bayesian Agent-Based Modeling/Evidence
Method evidence record

Bayesian Agent-Based Modeling

Bayesian Agent-Based Modeling integrates Bayesian statistical inference with agent-based simulation to calibrate model parameters and quantify uncertainty. Rather than fixing agent rules and parameters by assumption, this approach treats unknown parameters as probability distributions and updates them systematically against observed data, yielding a full posterior over plausible model configurations.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Bayesian Agent-Based Modeling — Parameter Estimation and Uncertainty Quantification for Agent-Based Models
Taxonomic method record · process-pipeline / simulation
  • Sunnaker, M., Busetto, A. G., Numminen, E., Corander, J., Foll, M., Dessimoz, C. (2013). Approximate Bayesian Computation. PLOS Computational Biology, 9(1), e1002803. · DOI 10.1371/journal.pcbi.1002803
  • Grazzini, J., Richiardi, M. (2015). Estimation of agent-based models by simulated minimum distance. Journal of Economic Dynamics and Control, 51, 148-165. · DOI 10.1016/j.jedc.2014.10.006
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyApproximate Bayesian Computationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Markov Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Microsimulationmachine-suggested · Relational suggestion, not evidence.See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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