ABSTRACT
Sensitivity analysis is the study of how uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model input (Saltelli et al. 2004). Sometimes the term is also used to indicate simply the quantification of the uncertainty in the model’s prediction, although strictly speaking, this is the closely related discipline of uncertainty analysis. In general, sensitivity analysis is used to test the robustness of
of Design and Analysis of
model-based inference, that is, how much the results of the model depend on the assumptions made in its construction and in particular on the specification of model input values. In engineering and risk analysis, sensitivity analysis mostly involves an exploration of the multidimensional space of the input variables.
