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Estimating the Approximation Error when Fixing Unessential Factors in Global Sensitivity Analysis

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One of the major settings of global sensitivity analysis is that of fixing non influential factors, in order to reduce the dimensionality of a model. However, this is usually done without knowing the magnitude of the approximation error being produced. This paper presents and proves a new theorem for the estimation of the average approximation error generated when fixing non influential factors. A simple function where analytical solutions are available is used as test case to illustrate the theorem; furthermore this function is used to show the theorem applicability to sensitivity analysis by groups of factors. Improved formulas for the estimation of sensitivity indices are presented; such formulas allow for more accurate estimations at a lower computational cost with respect to the original method of Sobol’.
2007-04-10
ELSEVIER SCI LTD
JRC33269
https://publications.jrc.ec.europa.eu/repository/handle/JRC33269,   
10.1016/j.ress.2006.07.001,   
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