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On global sensitivity analysis of quasi-Monte Carlo algorithms

Author

Listed:
  • Sobol´ I.M.

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

  • Kucherenko S.S.

    (2. Imperial College London, SW7 2AZ, UK)

Abstract

Different Quasi-Monte Carlo algorithms corresponding to the same Monte Carlo algorithm are considered. Even in the case when their constructive dimensions are equal and the same quasi-random points are used, the efficiencies of these algorithms may differ. Global sensitivity analysis provides an insight into this situation. As a model problem two well-known approximations of a Wiener integral are considered: the standard one and the Brownian bridge. The advantage of the Brownian bridge is confirmed.

Suggested Citation

  • Sobol´ I.M. & Kucherenko S.S., 2005. "On global sensitivity analysis of quasi-Monte Carlo algorithms," Monte Carlo Methods and Applications, De Gruyter, vol. 11(1), pages 83-92, March.
    • Handle: RePEc:bpj:mcmeap:v:11:y:2005:i:1:p:83-92:n:4
    DOI: 10.1515/1569396054027274
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    Citations

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    Cited by:

    1. Julien Hok & Sergei Kucherenko, 2021. "Pricing and Risk Analysis in Hyperbolic Local Volatility Model with Quasi Monte Carlo," Papers 2106.08421, arXiv.org.
    2. Annoni, Paola & Bruggemann, Rainer & Saltelli, Andrea, 2012. "Random and quasi-random designs in variance-based sensitivity analysis for partially ordered sets," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 184-189.
    3. Zentner, Irmela & Tarantola, Stefano & de Rocquigny, E., 2011. "Sensitivity analysis for reliable design verification of nuclear turbosets," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 391-397.
    4. Weirs, V. Gregory & Kamm, James R. & Swiler, Laura P. & Tarantola, Stefano & Ratto, Marco & Adams, Brian M. & Rider, William J. & Eldred, Michael S., 2012. "Sensitivity analysis techniques applied to a system of hyperbolic conservation laws," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 157-170.
    5. Xiaoyan Zhu & Way Kuo, 2014. "Importance measures in reliability and mathematical programming," Annals of Operations Research, Springer, vol. 212(1), pages 241-267, January.
    6. Céline Diebold, 2022. "How Meaningful is the Elite Quality Index Ranking?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 137-170, August.
    7. Song, Shufang & Zhou, Tong & Wang, Lu & Kucherenko, Sergei & Lu, Zhenzhou, 2019. "Derivative-based new upper bound of Sobol’ sensitivity measure," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 142-148.
    8. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.

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