A review on global sensitivity analysis methods

  title={A review on global sensitivity analysis methods},
  author={Bertrand Iooss and Paul Lem{\^a}ıtre},
This chapter makes a review, in a complete methodological framework, of various global sensitivity analysis methods of model output. Numerous statistical and probabilistic tools (regression, smoothing, tests, statistical learning, Monte Carlo, . . . ) aim at determining the model input variables which mostly contribute to an interest quantity depending on model output. This quantity can be for instance the variance of an output variable. Three kinds of methods are distinguished: the screening… CONTINUE READING
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