Monte Carlo algorithms for evaluating Sobol’ sensitivity indices

I. Dimov and R. Georgieva

Mathematics and Computers in Simulation (MATCOM), 2010, vol. 81, issue 3, 506-514

Abstract: Sensitivity analysis is a powerful technique used to determine robustness, reliability and efficiency of a model. The main problem in this procedure is the evaluating total sensitivity indices that measure a parameter’s main effect and all the interactions involving that parameter. From a mathematical point of view this problem is presented by a set of multidimensional integrals. In this work a simple adaptive Monte Carlo technique for evaluating Sobol’ sensitivity indices is developed. A comparison of accuracy and complexity of plain Monte Carlo and adaptive Monte Carlo algorithms is presented. Numerical experiments for evaluating integrals of different dimensions are performed.

Keywords: Sensitivity analysis; Global sensitivity indices; Multidimensional numerical integration; Adaptive Monte Carlo algorithm (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:81:y:2010:i:3:p:506-514

DOI: 10.1016/j.matcom.2009.09.005

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