Uncertainty Analysis for Functional Computer Output: A Simulation Study in Inverse Problems

摘要

Computer models with functional output are omnipresent throughout science and engineering. Most often the computer model is treated as a black-box and information about the underlying mathematical model is not exploited in statistical analyses. Consequently, general-purpose bases such as wavelets are typically used to describe the main characteristics of the functional output. In this article we advocate for using information about the underlying mathematical model in order to choose a better basis for the functional output. To validate this choice, a simulation study is presented in the context of uncertainty analysis for a computer model from inverse Sturm-Liouville problems.