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Local Polynomial Estimation for Sensitivity Analysis on Models With Correlated Inputs

Summary: [This abstract is based on the authors' abstract.] When the inputs of a model are not independent, sensitivity indexes are derived from local polynomial techniques. Two original estimators based on local polynomial smoothers are proposed that have good theoretical properties and compare favorably with an earlier Bayesian approach. The proposed estimators are used to carry out a sensitivity analysis on real case models with correlated parameters.

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  • Topics: Process Capability, Problem Solving, Design of Experiments
  • Keywords: Moment estimation, Sensitivity analysis, Regression analysis, Nonparametric methods
  • Author: Da Veiga, Sebastien; Wahl, Francois; Gamboa, Fabrice
  • Journal: Technometrics