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Derivative based global sensitivity measures

65 citations0/0 files storedProcedia - Social and Behavioral Sciences

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Probabilistic and Robust Engineering Design Mathematical Approximation and Integration Gaussian Processes and Bayesian Inference

Abstract

We introduce new global sensitivity measures called derivative based global sensitivity measures (DGSM). We also show that there is a link between DGSM and Sobol’ total sensitivity indices which makes this approach theoretically sound and general. It can be seen as the generalization of the Morris method. The computational time required for numerical evaluation of DGSM can be much lower than that for estimation of the Sobol’ sensitivity indices although it is problem dependent. The efficiency of the method can be further improved by using the automatic differentiation algorithm for calculation DGSM.

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References

2007Global Sensitivity Analysis. The Primer 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates 1991Factorial Sampling Plans for Preliminary Computational Experiments 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index 2002Making best use of model evaluations to compute sensitivity indices 2007An effective screening design for sensitivity analysis of large models 1996Importance measures in global sensitivity analysis of nonlinear models 1999Analysis of variance designs for model output

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