Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Confidence intervals for sensitivity indices using reduced-basis metamodels

Alexandre Janon 1, 2, * Maëlle Nodet 1 Clémentine Prieur 1, 2
* Corresponding author
1 MOISE - Modelling, Observations, Identification for Environmental Sciences
Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann, Inria Grenoble - Rhône-Alpes
Abstract : Global sensitivity analysis is often impracticable for complex and time demanding numerical models, as it requires a large number of runs. The reduced-basis approach provides a way to replace the original model by a much faster to run code. In this paper, we are interested in the information loss induced by the approximation on the estimation of sensitivity indices. We present a method to provide a robust error assessment, hence enabling significant time savings without sacrifice on precision and rigourousness. We illustrate our method with an experiment where computation time is divided by a factor of nearly 6. We also give directions on tuning some of the parameters used in our estimation algorithms.
Complete list of metadata
Contributor : Alexandre Janon Connect in order to contact the contributor
Submitted on : Tuesday, February 22, 2011 - 1:33:15 PM
Last modification on : Saturday, November 13, 2021 - 6:10:04 PM
Long-term archiving on: : Tuesday, November 6, 2012 - 2:40:59 PM


Files produced by the author(s)


  • HAL Id : inria-00567977, version 1
  • ARXIV : 1102.4668


Alexandre Janon, Maëlle Nodet, Clémentine Prieur. Confidence intervals for sensitivity indices using reduced-basis metamodels. 2011. ⟨inria-00567977v1⟩



Les métriques sont temporairement indisponibles