Sensitivity analysis practices: Strategies for model-based inference
Sensitivity analysis practices: Strategies for model-based inference
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DOI：
10.1016/j.ress.2005.11.014
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发表时间：
2006-10-01
影响因子：
8.1
通讯作者：
Campolongo, Francesca
中科院分区：
文献类型：
--
作者：
Saltelli, Andrea;Ratto, Marco;Campolongo, Francesca
在1989年《科学》杂志对敏感度分析(SA)方法的回顾(H.Rabitz所著的《分子尺度的系统分析》)发表14年后，我们在线检索《科学》杂志，以确定并回顾所有最近的文章，这些文章的关键词都是《敏感度分析》。尽管这一学科取得了长足的发展，出现了良好的做法，大西洋两岸都发布了关于SA的现有准则，但在我们的审查中，我们找不到其他非常原始的SA工具，这些工具是基于“一次一个因素”(OAT)的方法。在模型确证或证伪的情况下，我们证明这种OAT方法的使用是非法和不正当的，除非被分析的模型被证明是线性的。我们表明，现有的良好实践，如基于方差的度量和其他方法，能够克服OAT的缺点，并且易于实现。这些方法还允许严格定义因素重要性的概念，从而使因素重要性排序变得单调。我们在建模的背景下分析了SA的需求，并在基本模型的基础上提出了最佳可用实践。我们还向读者指出了严格SA的可用食谱。(C)2005爱思唯尔有限公司。保留所有权利。
Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having "sensitivity analysis" as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on "one-factor-at-a-time" (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA. (c) 2005 Elsevier Ltd. All rights reserved.