Please use this identifier to cite or link to this item:
|Title:||Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index|
|Authors:||SALTELLI Andrea; ANNONI Paola; AZZINI Ivano; CAMPOLONGO Francesca; RATTO Marco; TARANTOLA Stefano|
|Citation:||COMPUTER PHYSICS COMMUNICATIONS vol. 181 no. 2 p. 259-270|
|Publisher:||ELSEVIER SCIENCE BV|
|Type:||Articles in Journals|
|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:||Institute for the Protection and Security of the Citizen|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.