Title: Estimation of global sensitivity indices for models with dependent variables
Authors: KUCHERENKO SergeiTARANTOLA StefanoANNONI Paola
Citation: COMPUTER PHYSICS COMMUNICATIONS vol. 183 no. 4 p. 937-946
Publisher: ELSEVIER SCIENCE BV
Publication Year: 2012
JRC Publication N°: JRC64266
ISSN: 0010-4655
URI: http://www.sciencedirect.com/science/article/pii/S0010465511004085
http://publications.jrc.ec.europa.eu/repository/handle/JRC64266
DOI: 10.1016/j.cpc.2011.12.020
Type: Articles in Journals
Abstract: A novel approach to estimate variance based sensitivity indices for the case of correlated variables is presented. Both the first order and total sensitivity indices are derived as generalizations of Sobol’ sensitivity indices. Formulas and Monte Carlo numerical estimates similar to Sobol’ formulas are derived. A Gaussian copula based approach to sampling from multivariate probability distributions is proposed. The method is shown to quickly reach convergence and to be faster than the so-called brute force method. A good agreement between analytical and numerical values of the first order and total indices for two test cases is obtained. A third test case, including both correlation and interaction among input variables, shows that the behaviour of sensitivity indices depends on the relative predominance of interaction and correlation.
JRC Institute:Institute for the Protection and Security of the Citizen

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