基于方差的数值模式全局敏感性分析
Variance-based global sensitivity analysis of numerical models using R
摘要：
敏感性分析通过识别每个（不确定）输入因素对模型输出可变性的贡献，在计算机模型/模拟器的开发中发挥着重要作用。本报告调查不同方面的方差为基础的全球敏感性分析的背景下，复杂的黑箱计算机代码。该分析主要使用两个R包进行，即sensobol（Puy et al.，2021）和灵敏度（Looss等人，2021年）。虽然软件包灵敏度配备了一套丰富的方法来进行敏感性分析，特别是在模型与相关输入的情况下，软件包sensobol提供了一堆用户友好的可视化工具。提供了几个说明性的例子，使用户能够轻松地学习这两个包，并从它们的功能中受益。
英文摘要：
Sensitivity analysis plays an important role in the development of computer models/simulators through identifying the contribution of each (uncertain) input factor to the model output variability. This report investigates different aspects of the variance-based global sensitivity analysis in the context of complex black-box computer codes. The analysis is mainly conducted using two R packages, namely sensobol (Puy et al., 2021) and sensitivity (Iooss et al., 2021). While the package sensitivity is equipped with a rich set of methods to conduct sensitivity analysis, especially in the case of models with dependent inputs, the package sensobol offers a bunch of user-friendly tools for the visualisation purposes. Several illustrative examples are supplied that allow the user to learn both packages easily and benefit from their features.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
