Sensitivity indexes when the inputs of a model are not independent are derived from local polynomial techniques. Two original estimators based on local polynomial smoothers are proposed. Both have good theoretical properties, which are illustrated through analytical examples. Comparison with the Bayesian approach developed by Oakley and O’Hagan (2004) is also performed. The two proposed estimators are used to carry out a sensitivity analysis on two real case models with correlated parameters.
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Veiga et al. (2009) studied this question.
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