Confidence intervals for sensitivity indices using reduced-basis metamodels

Details Confidence intervals for sensitivity indices using reduced-basis metamodels Confidence intervals for sensitivity indices using reduced-basis metamodels

2011-02-23

arxiv.org/abs/1102.4668v1

Statistics

Computation

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Confidence intervals for sensitivity indices using reduced-basis metamodels does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Confidence intervals for sensitivity indices using reduced-basis metamodels, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Confidence intervals for sensitivity indices using reduced-basis metamodels will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-174289