Title: Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
Citation: COMPUTER PHYSICS COMMUNICATIONS vol. 181 no. 2 p. 259-270
Publication Year: 2010
JRC N°: JRC52955
ISSN: 0010-4655
URI: www.elsevier.com/locate/cpc
DOI: 10.1016/j.cpc.2009.09.018
Type: Articles in periodicals and books
Abstract: Variance based methods have assessed themselves as versatile and effective among the various available techniques for sensitivity analysis of model output. Practitioners can in principle describe the sensitivity pattern of a model Y=f ( X_1,X_2,... X_k) with k uncertain input factors via a full decomposition of the variance V(Y) of Y into terms depending on the factors and their interactions. More often practitioners are satisfied with computing just k first order effects and k total effects, the latter describing synthetically interactions among input factors. In sensitivity analysis a key concern is the computational cost of the analysis, defined in terms of number of evaluations of f ( X_1,X_2,... X_k) needed to complete the analysis, as f ( X_1,X_2,... X_k) is often in the form of a numerical model which may take long processing time. While the computational cost is relatively cheap and k-independent for estimating first order effects, it remains expensive and k-dependent for total effect indices. In the present note we compare existing and new practices for this index and offer recommendations on which to use.
JRC Institute:Space, Security and Migration

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