Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Analisi di Sensibilità degli Scenari di Policy× | Simulazione Monte Carlo× | |
|---|---|---|
| Campo≠ | Simulazione | Processo decisionale |
| Famiglia≠ | Process / pipeline | MCDM |
| Anno di origine≠ | 1990s–2000s | 1949 |
| Ideatore≠ | Saltelli, A. et al.; Lempert, R. J. et al. | Metropolis, N., Ulam, S. |
| Tipo≠ | Analytical framework combining scenario planning with sensitivity analysis | Robustness wrapper — Monte Carlo uncertainty propagation |
| Fonte seminale≠ | Saltelli, 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: 9780470059975 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Alias≠ | PSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis | — |
| Correlati≠ | 5 | 0 |
| Sintesi≠ | Policy 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. |
| ScholarGateInsieme di dati ↗ |
|
|