Abstract
Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input–output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based modeling, the aim is to fill the response or feature space. In this article, we propose a new experimental design framework that aims to sequentially fill the space of the outputs (responses or features). Several examples are given to show the advantages of the proposed method over the traditional input space-filling designs.
Supplementary Materials
Algorithms and additional results: The statements of Algorithms 1–5 are given in the file appendix.pdf along with some additional results.
Codes: The R codes to reproduce and an R Markdown tutorial are included in a zip file. The implementation of the algorithms is available in the R package OSFD (Wang and Joseph Citation2023).
Disclosure Statement
The authors report there are no competing interests to declare.