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Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition

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  • Sinan Xiao
  • Zhenzhou Lu
  • Pan Wang

Abstract

In this article, a new set of multivariate global sensitivity indices based on distance components decomposition is proposed. The proposed sensitivity indices can be considered as an extension of the traditional variance‐based sensitivity indices and the covariance decomposition‐based sensitivity indices, and they have similar forms. The advantage of the proposed sensitivity indices is that they can measure the effects of an input variable on the whole probability distribution of multivariate model output when the power of distance 0

Suggested Citation

  • Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    • Handle: RePEc:wly:riskan:v:38:y:2018:i:12:p:2703-2721
    DOI: 10.1111/risa.13133
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    Cited by:

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    8. Ma, Yuan-Zhuo & Jin, Xiang-Xiang & Zhao, Xiang & Li, Hong-Shuang & Zhao, Zhen-Zhou & Xu, Chang, 2024. "Reliability-oriented global sensitivity analysis using subset simulation and space partition," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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