Sensitivity indices for independent groups of variables

Baptiste Broto, François Bachoc, Marine Depecker and Jean-Marc Martinez

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 163, issue C, 19-31

Abstract: In this paper, we study sensitivity indices for independent groups of variables and we look at the particular case of block-additive models. We show in this case that most of the Sobol indices are equal to zero and that Shapley effects can be estimated more efficiently. We then apply this study to Gaussian linear models, and we provide an efficient algorithm to compute the theoretical sensitivity indices. In numerical experiments, we show that this algorithm compares favourably to other existing methods. We also use the theoretical results to improve the estimation of the Shapley effects for general models, when the inputs form independent groups of variables.

Keywords: Global sensitivity analysis; Sobol indices; Shapley effects (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:163:y:2019:i:c:p:19-31

DOI: 10.1016/j.matcom.2019.02.008

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