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Functional principal component analysis for global sensitivity analysis of model with spatial output

Author

Listed:
  • Perrin, T.V.E.
  • Roustant, O.
  • Rohmer, J.
  • Alata, O.
  • Naulin, J.P.
  • Idier, D.
  • Pedreros, R.
  • Moncoulon, D.
  • Tinard, P.

Abstract

Motivated by risk assessment of coastal flooding, we consider time-consuming simulators with a spatial output. The aim is to perform sensitivity analysis (SA), quantifying the influence of input parameters on the output. There are three main issues. First, due to computational time, standard SA techniques cannot be directly applied on the simulator. Second, the output is infinite dimensional, or at least high dimensional if the output is discretized. Third, the spatial output is non-stationary and exhibits strong local variations.

Suggested Citation

  • Perrin, T.V.E. & Roustant, O. & Rohmer, J. & Alata, O. & Naulin, J.P. & Idier, D. & Pedreros, R. & Moncoulon, D. & Tinard, P., 2021. "Functional principal component analysis for global sensitivity analysis of model with spatial output," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:reensy:v:211:y:2021:i:c:s0951832021000831
    DOI: 10.1016/j.ress.2021.107522
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    References listed on IDEAS

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    1. Li, Min & Wang, Ruo-Qian & Jia, Gaofeng, 2020. "Efficient dimension reduction and surrogate-based sensitivity analysis for expensive models with high-dimensional outputs," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Dupuy, Delphine & Helbert, Céline & Franco, Jessica, 2015. "DiceDesign and DiceEval: Two R Packages for Design and Analysis of Computer Experiments," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i11).
    3. Lamboni, Matieyendou & Monod, Hervé & Makowski, David, 2011. "Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 450-459.
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    2. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    3. Xiong, Qingwen & Du, Peng & Deng, Jian & Huang, Daishun & Song, Gongle & Qian, Libo & Wu, Zenghui & Luo, Yuejian, 2022. "Global sensitivity analysis for nuclear reactor LBLOCA with time-dependent outputs," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
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    5. López-Lopera, Andrés F. & Idier, Déborah & Rohmer, Jérémy & Bachoc, François, 2022. "Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

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