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क्षेत्रअनुकरणनिर्णयन
परिवारProcess / pipelineMCDM
उद्भव वर्ष1990s–2000s2004
प्रवर्तकDeveloped within health economics and policy modeling communities; foundational work by Briggs, Claxton, and SculpherSaltelli, A., Tarantola, S., Campolongo, F., Ratto, M.
प्रकारProbabilistic scenario simulationRobustness wrapper — parameter / weight perturbation sensitivity indices
मौलिक स्रोतBriggs, A. H., Claxton, K., & Sculpher, M. J. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. ISBN: 9780198526629Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗
उपनामPS-MCS, Policy MC Simulation, Scenario-Based Monte Carlo, Policy Uncertainty Simulation
संबंधित40
सारांशPolicy 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.SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateविधियों की तुलना करें: Policy Scenario Monte Carlo Simulation · SENSITIVITY-ANALYSIS. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare