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Bayesian Microsimulation

Bayesian Microsimulation combines individual-level simulation of heterogeneous populations with Bayesian statistical inference. Each synthetic individual follows a probabilistic life path, while model parameters are governed by prior beliefs updated with observed data. This approach is widely used in health technology assessment, public policy costing, and demographic projection, where uncertainty in both model inputs and structural assumptions must be formally quantified and propagated through to output estimates.

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Bayesian Microsimulation — Probabilistic individual-level simulation with Bayesian parameter estimation

Dossier de méthode taxonomique · process-pipeline / simulation

Williamson, P., Birkin, M., & Rees, P. H. (2000). The estimation of population microdata by using data from small area statistics and samples of anonymised records. Environment and Planning A, 30(5), 785-816. · DOI 10.1068/a300785
Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. John Wiley & Sons. · ISBN 9780471499756

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Taxonomic bucketAgent-based microsimulationmachine-suggested · Relational suggestion, not evidence.See alsoBayesian Inferencemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMarkov Modelmachine-suggested · Relational suggestion, not evidence.Same method familyMicrosimulationmachine-suggested · Relational suggestion, not evidence.See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStochastic Microsimulationmachine-suggested · Relational suggestion, not evidence.