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Calculations of Sobol indices for the Gaussian process metamodel

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  1. Chen, Gaolin & Zhou, Shuming & Li, Min & Zhang, Hong, 2022. "Evaluation of community vulnerability based on communicability and structural dissimilarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
  2. Zio, E. & Pedroni, N., 2012. "Monte Carlo simulation-based sensitivity analysis of the model of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 90-106.
  3. Wu, Xu & Kozlowski, Tomasz & Meidani, Hadi, 2018. "Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 422-436.
  4. Lambert, Romain S.C. & Lemke, Frank & Kucherenko, Sergei S. & Song, Shufang & Shah, Nilay, 2016. "Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 128(C), pages 42-54.
  5. Ballester-Ripoll, Rafael & Leonelli, Manuele, 2022. "Computing Sobol indices in probabilistic graphical models," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
  6. Fissler, Tobias & Pesenti, Silvana M., 2023. "Sensitivity measures based on scoring functions," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1408-1423.
  7. Deman, G. & Konakli, K. & Sudret, B. & Kerrou, J. & Perrochet, P. & Benabderrahmane, H., 2016. "Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 156-169.
  8. Qian, Gengjian & Massenzio, Michel & Brizard, Denis & Ichchou, Mohamed, 2019. "Sensitivity analysis of complex engineering systems: Approaches study and their application to vehicle restraint system crash simulation," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 110-118.
  9. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
  10. Zhang, Dequan & Liang, Hongyi & Li, Xing-ao & Jia, Xinyu & Wang, Fang, 2025. "Kinematic calibration of industrial robot using Bayesian modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
  11. Pronzato, Luc, 2019. "Sensitivity analysis via Karhunen–Loève expansion of a random field model: Estimation of Sobol’ indices and experimental design," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 93-109.
  12. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
  13. Kucherenko, S. & Delpuech, B. & Iooss, B. & Tarantola, S., 2015. "Application of the control variate technique to estimation of total sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 251-259.
  14. Marrel, Amandine & Chabridon, Vincent, 2021. "Statistical developments for target and conditional sensitivity analysis: Application on safety studies for nuclear reactor," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  15. Xuefei Lu & Alessandro Rudi & Emanuele Borgonovo & Lorenzo Rosasco, 2020. "Faster Kriging: Facing High-Dimensional Simulators," Operations Research, INFORMS, vol. 68(1), pages 233-249, January.
  16. Kucherenko, S. & Song, S., 2017. "Different numerical estimators for main effect global sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 222-238.
  17. Wang, Zeyu & Shafieezadeh, Abdollah, 2020. "On confidence intervals for failure probability estimates in Kriging-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
  18. Blatman, Géraud & Sudret, Bruno, 2010. "Efficient computation of global sensitivity indices using sparse polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1216-1229.
  19. Echard, B. & Gayton, N. & Lemaire, M. & Relun, N., 2013. "A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 232-240.
  20. Roustant, O. & Fruth, J. & Iooss, B. & Kuhnt, S., 2014. "Crossed-derivative based sensitivity measures for interaction screening," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 105(C), pages 105-118.
  21. Daneshkhah, A. & Stocks, N.G. & Jeffrey, P., 2017. "Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 33-45.
  22. Steiner, M. & Bourinet, J.-M. & Lahmer, T., 2019. "An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 323-340.
  23. F. Grelot & J. Arnal & Pauline Bremond & Katrin Erdlenbruch & C. Durand & S. Durand & G. Gleyses & P. Jarnet & M. Liberti & S. Martini & A. Richard-Ferroudji & Laurent Albrech & Jean-Stéphane Bailly &, 2009. "Risk perception and economic valuation of flood exposure. Study of two hydrologically contrasted territories [Perception du risque et évaluation économique de l'exposition aux inondations. Étude de deux territoires aux contextes hydrologiques diff," Working Papers hal-02593242, HAL.
  24. Kapusuzoglu, Berkcan & Mahadevan, Sankaran, 2021. "Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  25. Wan, Zhiqiang & Wang, Silong & Wu, Ziyan & Wang, Xiuli, 2025. "Dimension-independent single-loop Monte Carlo simulation method for estimate of Sobol’ indices in variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 263(C).
  26. Durrande, N. & Ginsbourger, D. & Roustant, O. & Carraro, L., 2013. "ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 57-67.
  27. Xiao, Sinan & Oladyshkin, Sergey & Nowak, Wolfgang, 2020. "Reliability analysis with stratified importance sampling based on adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  28. Tabandeh, Armin & Sharma, Neetesh & Gardoni, Paolo, 2022. "Uncertainty propagation in risk and resilience analysis of hierarchical systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  29. Geoffrey Fairchild & Kyle S. Hickmann & Susan M. Mniszewski & Sara Y. Del Valle & James M. Hyman, 2014. "Optimizing human activity patterns using global sensitivity analysis," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 394-416, December.
  30. Zio, E. & Pedroni, N., 2009. "Functional failure analysis of a thermal–hydraulic passive system by means of Line Sampling," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1764-1781.
  31. Francesco Di Maio & Nicola Pedroni & Barnabás Tóth & Luciano Burgazzi & Enrico Zio, 2021. "Reliability Assessment of Passive Safety Systems for Nuclear Energy Applications: State-of-the-Art and Open Issues," Energies, MDPI, vol. 14(15), pages 1-17, August.
  32. Ballester-Ripoll, Rafael & Paredes, Enrique G. & Pajarola, Renato, 2019. "Sobol tensor trains for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 311-322.
  33. Konakli, Katerina & Sudret, Bruno, 2016. "Global sensitivity analysis using low-rank tensor approximations," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 64-83.
  34. Girard, Sylvain & Romary, Thomas & Favennec, Jean-Melaine & Stabat, Pascal & Wackernagel, Hans, 2013. "Sensitivity analysis and dimension reduction of a steam generator model for clogging diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 143-153.
  35. Liu, Yaning & Yousuff Hussaini, M. & Ökten, Giray, 2016. "Accurate construction of high dimensional model representation with applications to uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 281-295.
  36. 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).
  37. Wei, Daijun & Zhang, Xiaoge & Mahadevan, Sankaran, 2018. "Measuring the vulnerability of community structure in complex networks," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 41-52.
  38. Azzini, Ivano & Rosati, Rossana, 2021. "Sobol’ main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
  39. Heredia, María Belén & Prieur, Clémentine & Eckert, Nicolas, 2021. "Nonparametric estimation of aggregated Sobol’ indices: Application to a depth averaged snow avalanche model," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
  40. Lamoureux, Benjamin & Mechbal, Nazih & Massé, Jean-Rémi, 2014. "A combined sensitivity analysis and kriging surrogate modeling for early validation of health indicators," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 12-26.
  41. Pedroni, N. & Zio, E. & Apostolakis, G.E., 2010. "Comparison of bootstrapped artificial neural networks and quadratic response surfaces for the estimation of the functional failure probability of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 386-395.
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