Functional ANOVA in Computer Models With Time Series Output
Functional ANOVA in Computer Models With Time Series Output
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DOI：
10.1198/tech.2010.10029
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发表时间：
2010-11
期刊：
影响因子：
2.5
通讯作者：
Dorin Drignei
中科院分区：
文献类型：
--
作者：
Dorin Drignei
计算机模型是科学研究自然现象的重要工具。一个计算机模型可以被看作是一个输入→输出函数。为了评估每个输入对输出的影响，通常进行正式的敏感性分析。本文中讨论的一种特定类型的敏感性分析是函数ANOVA，其中使用输出方差分解来量化每个输入的重要性。在这里，我们提出了功能方差分析的计算机模型与时间序列输出。本文的论证来源于条件期望和时间方差的概念。我们还建立了建议的敏感性指标和文献中存在的全局正则敏感性指标之间的关系。汽车行业的应用程序来说明的方法。
Computer models are important tools used in scientific investigations of natural phenomena. A computer model may be viewed as an input → output function. In order to assess the influence of each input on the output, formal sensitivity analyses are typically carried out. A specific type of sensitivity analysis addressed in this article is the functional ANOVA, in which an output variance decomposition is used to quantify each input’s importance. Here we propose functional ANOVA for computer models with time series output. The argument given in this article originates in the concept of conditional expectation and variance with respect to time. We also establish a relationship between the proposed sensitivity indices and the global regular sensitivity indices existent in the literature. An application from the automotive industry is presented to illustrate the methods.