A comparison of two sampling methods for global sensitivity analysis
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 general, the Sobol’ design performs better, however the Latin supercube sampling design appears to offer advantages in specific cases, such as smaller sample sizes and medium dimensionality.
TARANTOLA Stefano;
BECKER William Edward;
ZEITZ Dirk;
2012-07-06
ELSEVIER SCIENCE BV
JRC64877
0010-4655,
http://www.sciencedirect.com/science/article/pii/S0010465511004036,
https://publications.jrc.ec.europa.eu/repository/handle/JRC64877,
10.1016/j.cpc.2011.12.015,
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