方法对比
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| 确定性情景分析× | 确定性敏感性分析× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1967 | 1950s–1970s (formalized) |
| 提出者≠ | Kahn, H., Wiener, A. J. (RAND Corporation / Hudson Institute) | Saltelli, A. et al.; widely formalized across operations research and health economics |
| 类型≠ | Exploratory planning and decision-support framework | Parameter variation / robustness testing |
| 开创性文献≠ | Kahn, H., Wiener, A. J. (1967). The Year 2000: A Framework for Speculation on the Next Thirty-Three Years. Macmillan, New York. ISBN: 9780025604407 | Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. ISBN: 9780470870938 |
| 别名 | DSA, Fixed-Input Scenario Analysis, Classical Scenario Analysis, Deterministic What-If Analysis | DSA, One-Way Sensitivity Analysis, Tornado Diagram Analysis, Parametric Sensitivity Analysis |
| 相关≠ | 5 | 2 |
| 摘要≠ | Deterministic Scenario Analysis (DSA) is a structured planning method in which analysts construct a finite set of internally consistent future scenarios, each defined by fixed, precisely specified parameter values rather than probability distributions. By running a model or calculation under each scenario's fixed inputs, decision-makers can map how outcomes diverge across plausible futures and stress-test strategies without requiring full probabilistic characterization of uncertainty. | Deterministic Sensitivity Analysis (DSA) tests how model outputs change when individual or combined input parameters are varied across plausible ranges, one at a time or in structured combinations, without invoking probabilistic sampling. It is the standard approach in economic modeling, decision trees, and mathematical programming to identify which parameters drive conclusions and to demonstrate model robustness to regulators, reviewers, and stakeholders. |
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