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Analýza citlivosti politických scénářů×Simulace Monte Carlo×
OborSimulaceRozhodování
RodinaProcess / pipelineMCDM
Rok vzniku1990s–2000s1949
TvůrceSaltelli, A. et al.; Lempert, R. J. et al.Metropolis, N., Ulam, S.
TypAnalytical framework combining scenario planning with sensitivity analysisRobustness wrapper — Monte Carlo uncertainty propagation
Původní zdrojSaltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. John Wiley & Sons, Chichester. ISBN: 9780470059975Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Další názvyPSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis
Příbuzné50
ShrnutíPolicy Scenario Sensitivity Analysis (PSSA) combines structured scenario planning with formal sensitivity analysis to determine which model inputs and policy parameters most strongly drive outcomes across a set of distinct policy alternatives or future states. It is widely used in public health, climate, energy, and economic policy modeling to identify robust interventions that perform well even when key assumptions vary.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGatePorovnat metody: Policy Scenario Sensitivity Analysis · MONTE-CARLO-SIMULATION. Získáno 2026-06-18 z https://scholargate.app/cs/compare