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On Global Sensitivity Indices: Monte Carlo Estimates Affected by Random Errors

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  • Sobol' Ilya M.

    (1. Institute for Mathematical Modelling, Russian Academy of Sciences, Miusskaya Square 4, Moscow 125047, Russia.)

  • Shukhman Boris V.

    (2. Borelsoft, Canada, Russia.)

Abstract

Global sensitivity indices for sensitivity analysis of model output are usually estimated by Monte Carlo or quasi-Monte Carlo methods. In this paper, the bias in sensitivity indices produced by random errors in model evaluation is studied.

Suggested Citation

  • Sobol' Ilya M. & Shukhman Boris V., 2007. "On Global Sensitivity Indices: Monte Carlo Estimates Affected by Random Errors," Monte Carlo Methods and Applications, De Gruyter, vol. 13(1), pages 89-97, April.
    • Handle: RePEc:bpj:mcmeap:v:13:y:2007:i:1:p:89-97:n:5
    DOI: 10.1515/MCMA.2007.005
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    References listed on IDEAS

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    1. Sobol’, I.M. & Tarantola, S. & Gatelli, D. & Kucherenko, S.S. & Mauntz, W., 2007. "Estimating the approximation error when fixing unessential factors in global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 92(7), pages 957-960.
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