Adaptively Sampling via Regional Variance-Based Sensitivities
Methodology
2021-07-21 v1 Applications
Abstract
Inspired by the well-established variance-based methods for global sensitivity analysis, we develop a local total sensitivity index that decomposes the global total sensitivity conditions by independent variables' values. We employ this local sensitivity index in a new method of experimental design that sequentially and adaptively samples the domain of a multivariate function according to local contributions to the global variance. The method is demonstrated on a nonlinear illustrative example that has a three-dimensional domain and a three-dimensional codomain, but also on a complex, high-dimensional simulation for assessing the industrial viability of the production of bioproducts from biomass.
Cite
@article{arxiv.2107.09538,
title = {Adaptively Sampling via Regional Variance-Based Sensitivities},
author = {Brian W. Bush and Joanne Wendelberger and Rebecca Hanes},
journal= {arXiv preprint arXiv:2107.09538},
year = {2021}
}
Comments
22 pages, 8 figures