A comparison of two sampling methods for global sensitivity analysis |
| |
| Authors: | Stefano Tarantola William Becker Dirk Zeitz |
| |
| Affiliation: | 1. School of Reliability and Systems Engineering, Beihang University (BUAA), No. 37 XueYuan Rd, Haidian, Beijing 100191, China;2. PCB Technology Center, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;1. Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, Wollgrasweg 43, 70593 Stuttgart, Germany;2. Department of Socio-Economic Sciences, Research Institute of Organic Agriculture (FiBL), Ackerstrasse 113, CH-5070 Frick, Switzerland |
| |
| Abstract: | We compare the convergence properties of two different quasi-random sampling designs – Sobol?s quasi-Monte Carlo, and Latin supercube sampling in variance-based global sensitivity analysis. We use the non-monotonic V-function of Sobol? as base case-study, and compare the performance of both sampling strategies at increasing sample size and dimensionality against analytical values. The results indicate that in almost all cases investigated here, the Sobol? design performs better. This, coupled with the fact that effective Latin supercube sampling requires a priori knowledge of the interaction properties of the function, leads us to recommend Sobol? sampling in most practical cases. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
