 A simple algorithm for global sensitivity analysis with Shapley effectsTakashi Goda Reliability Engineering and System Safety, 2021, vol. 213, issue C Abstract: Global sensitivity analysis aims at measuring the relative importance of different variables or groups of variables for the variability of a quantity of interest. Among several sensitivity indices, so-called Shapley effects have recently gained popularity mainly because the Shapley effects for all the individual variables are summed up to the overall variance, which gives a better interpretability than the classical sensitivity indices called main effects and total effects. In this paper, assuming that all the input variables are independent, we introduce a quite simple Monte Carlo algorithm to estimate the Shapley effects for all the individual variables simultaneously, which drastically simplifies the existing algorithms proposed in the literature. We present a short Matlab implementation of our algorithm and show some numerical results. A possible extension to the case where the input variables are dependent is also discussed. Keywords: Global sensitivity analysis; Shapley effect; Monte Carlo methods (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002374 DOI: 10.1016/j.ress.2021.107702 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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