论文标题
基于方差的全局灵敏度分析数值模型
Variance-based global sensitivity analysis of numerical models using R
论文作者
论文摘要
灵敏度分析通过确定每个（不确定的）输入因子对模型输出变异性的贡献，在计算机模型/模拟器的开发中起重要作用。该报告在复杂的黑盒计算机代码的背景下研究了基于方差的全局灵敏度分析的不同方面。该分析主要使用两个R包，即Sensobol（Puy等，2021）和灵敏度（IOOSS等，2021）。虽然软件包灵敏度配备了一系列可进行灵敏度分析的方法，尤其是在具有依赖输入的模型的情况下，Sensobol软件包为可视化目的提供了大量用户友好的工具。提供了几个说明性的示例，使用户可以轻松学习两个软件包并从其功能中受益。
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.
