方法对比
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| 政策情景敏感性分析× | 稳健性敏感性分析× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份 | 1990s–2000s | 1990s–2000s |
| 提出者≠ | Saltelli, A. et al.; Lempert, R. J. et al. | Saltelli, A. and colleagues |
| 类型≠ | Analytical framework combining scenario planning with sensitivity analysis | Simulation-based robustness assessment pipeline |
| 开创性文献≠ | 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 | 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 |
| 别名 | PSSA, Policy Sensitivity Analysis, Scenario-Based Sensitivity Analysis, Policy Robustness Analysis | RSA, Robust SA, Sensitivity Analysis under Uncertainty, Uncertainty-robust sensitivity analysis |
| 相关≠ | 5 | 3 |
| 摘要≠ | 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. | Robust Sensitivity Analysis (RSA) systematically evaluates how much variation in model outputs can be attributed to uncertainty or variation in model inputs, with an explicit focus on conclusions that remain valid across a wide range of plausible input conditions. It goes beyond standard sensitivity analysis by asking not only which inputs matter most, but which findings are truly robust — stable regardless of assumptions made under uncertainty. |
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