Monte Carlo estimators for small sensitivity indices

Sobol' I. M. and Myshetskaya E. E.
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Sobol' I. M.: Institute for Mathematical Modelling, Russian Academy of Sciences, Miusskaya Square 4, 125047 Moscow, Russia. Email: hq@imamod.ru
Myshetskaya E. E.: Institute for Mathematical Modelling, Russian Academy of Sciences, Miusskaya Square 4, 125047 Moscow, Russia. Email: hq@imamod.ru

Monte Carlo Methods and Applications, 2008, vol. 13, issue 5-6, 455-465

Abstract: The standard Monte Carlo algorithm for estimating global sensitivity indices may be spoilt by loss of accuracy if the index is very small. Two approaches were proposed for eliminating the loss of accuracy: reduction of the mean value and correlated sampling. In the present paper both approaches are investigated and a third combined approach is suggested.

Keywords: Sensitivity analysis; global sensitivity index; Monte Carlo method; variance estimates (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1515/mcma.2007.023

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