方法证据记录
Policy Scenario Monte Carlo Simulation
Policy Scenario Monte Carlo Simulation combines pre-defined discrete policy scenarios with probabilistic Monte Carlo sampling to quantify uncertainty in outcomes across each scenario. Rather than evaluating a single stochastic model, analysts define two or more policy alternatives and run thousands of Monte Carlo iterations within each, producing probability distributions of outcomes that support evidence-based policy comparison.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Policy Scenario Monte Carlo Simulation — Probabilistic uncertainty analysis across defined policy scenarios
分类方法记录 · process-pipeline / simulation
- Briggs, A. H., Claxton, K., & Sculpher, M. J. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. · ISBN 9780198526629
- Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. · ISBN 9780470059975
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