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Análise de Sensibilidade de Cenários de Políticas×Simulação de Monte Carlo×
ÁreaSimulaçãoTomada de decisão
FamíliaProcess / pipelineMCDM
Ano de origem1990s–2000s1949
Autor originalSaltelli, A. et al.; Lempert, R. J. et al.Metropolis, N., Ulam, S.
TipoAnalytical framework combining scenario planning with sensitivity analysisRobustness wrapper — Monte Carlo uncertainty propagation
Fonte seminalSaltelli, 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 ↗
Outros nomesPSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis
Relacionados50
ResumoPolicy 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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ScholarGateComparar métodos: Policy Scenario Sensitivity Analysis · MONTE-CARLO-SIMULATION. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare