Sixth International Conference on Sensitivity Analysis of Model Output How to avoid a perfunctory sensitivity analysis
Sixth International Conference on Sensitivity Analysis of Model Output How to avoid a perfunctory sensitivity analysis
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发表时间：
2010
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通讯作者：
Andrea Saltelli;P. Annoni
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文献类型：
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作者：
Andrea Saltelli;P. Annoni
文献中最流行的SA实践是“一次一个因素”（OAT）。这包括分析一次改变一个模型输入因子而保持所有其他因子不变的影响。虽然从统计文献中了解到OAT的缺点，但建模者广泛使用OAT引起了对相关敏感性分析质量的关注。我们介绍了一种新的几何证明OAT的效率低下，提供一个令人信服的，可能是明确的论点反对OAT的建模社区的目的。OAT的替代方案是基于统计理论，从实验设计，回归分析和敏感性分析适当的绘图。
The most popular SA practice seen in the literature is that of 'one-factor-at-a-time' (OAT). This consists of analyzing the effect of varying one model input factor at a time while keeping all other fixed. While the shortcomings of OAT are known from the statistical literature, its widespread use among modellers raises concern on the quality of the associated sensitivity analyses. We introduce a novel geometric proof of the inefficiency of OAT, with the purpose of providing the modelling community with a convincing and possibly definitive argument against OAT. Alternatives to OAT are indicated which are based on statistical theory, drawing from experimental design, regression analysis and sensitivity analysis proper.