RT Journal Article
ID 24a9e7176c18111a
A1 Lamboni, Matieyendou
T1 GLOBAL SENSITIVITY ANALYSIS: AN EFFICIENT NUMERICAL METHOD FOR APPROXIMATING THE TOTAL SENSITIVITY INDEX
JF International Journal for Uncertainty Quantification
JO IJUQ
YR 2016
FD 2016-08-16
VO 6
IS 1
SP 1
OP 17
K1 multivariate sensitivity analysis
K1 quadrature rules
K1 quasi-Monte Carlo
K1 total sensitivity indices
K1 variance-based sensitivity analysis
AB Variance-based sensitivity analysis and multivariate sensitivity analysis aim to apportion the variability of model output(s) into input factors and their interactions. Total sensitivity index (TSI) gives for each input its overall contribution, including the effects of its interactions with all the other inputs, in the variability of the model output(s). We investigate a numerical approximation of TSIs mainly based upon quadrature rules and quasi-Monte Carlo. The estimation of a TSI relies on the estimation of a total effect function (TEF), which allows for computing the TSI values by taking its variance. First, the paper derives the specific formula for the computation of the TEF, including the theoretical properties of the approximation, and second, it gives an overview of its application in many situations. Our approach gives the exact estimation of TSIs for a class of exact quadrature rules (especially for polynomial functions) and an interesting approximation for other functions. Numerical tests show the faster convergence rate of our approach and their usefulness in practice.
PB Begell House
LK http://dl.begellhouse.com/journals/52034eb04b657aea,6695b1fe0a01e538,24a9e7176c18111a.html