Work

Local Polynomial Estimation for Sensitivity Analysis on Models With Correlated Inputs

Year: 2009

Type: article

Abstract: 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.

Source: Technometrics

DOI: 10.1198/tech.2009.08124

Authors: Sebastien Da Veiga, Francois Wahl, Fabrice Gamboa

Institutions: Université Toulouse III - Paul Sabatier, Institut National des Sciences Appliquées de Toulouse, IFP Énergies nouvelles, Institut de Mathématiques de Toulouse, Université de Toulouse

Language: English

Topic: Probabilistic and Robust Engineering Design

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W1998634089

FWCI: 6.6

Cites: 19

Cited by: 125

Related to: 10