Non-parametric statistics in sensitivity analysis for model output : A comparison of selected techniquesFunded under: JRC-RADWASTE 5C
In this article a number of sensitivity analysis techniques are compared in the case of non-linear model responses. The test models originate from the context of the risk analysis for the disposal of radioactive waste, where sensitivity analysis plays a crucial role. All the techniques are applied to output from the same Monte Carlo simulations, where random sampling is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. Although the problem of relative efficiency is not touched upon explicitly, the estimators are ranked according to their robustness and stability for the test case under consideration, and qualitative differences in the prediction of the various tests are identified.
Bibliographic Reference: Article: Reliability Engineering and System Safety, Vol. 28 (1990) pp. 229-253
Record Number: 199210096 / Last updated on: 1994-12-02
Original language: en
Available languages: en