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Variance-based sensitivity indices for models with dependent inputs

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Cited by:

  1. Hu, Zhen & Mahadevan, Sankaran, 2019. "Probability models for data-Driven global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 40-57.
  2. Matieyendou Lamboni, 2020. "Uncertainty quantification: a minimum variance unbiased (joint) estimator of the non-normalized Sobol’ indices," Statistical Papers, Springer, vol. 61(5), pages 1939-1970, October.
  3. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
  4. Tianyang Wang & James S. Dyer & Warren J. Hahn, 2017. "Sensitivity analysis of decision making under dependent uncertainties using copulas," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 117-139, November.
  5. Pesenti, Silvana M. & Millossovich, Pietro & Tsanakas, Andreas, 2025. "Differential quantile-based sensitivity in discontinuous models," European Journal of Operational Research, Elsevier, vol. 322(2), pages 554-572.
  6. Ning-Cong Xiao & Hong-Zhong Huang & Yan-Feng Li & Zhonglai Wang & Xiao-Ling Zhang, 2013. "Non-probabilistic reliability sensitivity analysis of the model of structural systems with interval variables whose state of dependence is determined by constraints," Journal of Risk and Reliability, , vol. 227(5), pages 491-498, October.
  7. Zhang, Xiaodong & Dimitrov, Nikolay, 2024. "Variable importance analysis of wind turbine extreme responses with Shapley value explanation," Renewable Energy, Elsevier, vol. 232(C).
  8. Wang, Pan & Lu, Zhenzhou & Zhang, Kaichao & Xiao, Sinan & Yue, Zhufeng, 2018. "Copula-based decomposition approach for the derivative-based sensitivity of variance contributions with dependent variables," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 437-450.
  9. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
  10. 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).
  11. Viet Duong Nguyen, 2022. "Variance-based sensitivity analysis: non-parametric methods for weight optimization in composite indicators," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 76(4), pages 4-12, October-D.
  12. Zhou Changcong & Ji Mengyao & Zhao Haodong & Cao Fei, 2021. "Uncertainty analysis of motion error for mechanisms and Kriging-based solutions," Journal of Risk and Reliability, , vol. 235(5), pages 731-743, October.
  13. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
  14. 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).
  15. Surget, Charles & Dubreuil, Sylvain & Morio, Jérôme & Mattrand, Cécile & Bourinet, Jean-Marc & Gayton, Nicolas, 2025. "A sensitivity analysis based trade-off between probabilistic model identification and statistical estimation," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
  16. Horiguchi, Akira & Pratola, Matthew T. & Santner, Thomas J., 2021. "Assessing variable activity for Bayesian regression trees," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
  17. Broto, Baptiste & Bachoc, François & Depecker, Marine & Martinez, Jean-Marc, 2019. "Sensitivity indices for independent groups of variables," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 19-31.
  18. Pesenti, Silvana M. & Millossovich, Pietro & Tsanakas, Andreas, 2019. "Reverse sensitivity testing: What does it take to break the model?," European Journal of Operational Research, Elsevier, vol. 274(2), pages 654-670.
  19. 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).
  20. Jung, WoongHee & Taflanidis, Alexandros A., 2023. "Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
  21. Ge, Qiao & Menendez, Monica, 2017. "Extending Morris method for qualitative global sensitivity analysis of models with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 28-39.
  22. 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.
  23. López-Benito, Alfredo & Bolado-Lavín, Ricardo, 2017. "A case study on global sensitivity analysis with dependent inputs: The natural gas transmission model," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 11-21.
  24. Ismael Ahrazem Dfuf & José Manuel Mira McWilliams & María Camino González Fernández, 2019. "Multi-Output Conditional Inference Trees Applied to the Electricity Market: Variable Importance Analysis," Energies, MDPI, vol. 12(6), pages 1-24, March.
  25. Andreas Binder & Onkar Jadhav & Volker Mehrmann, 2021. "Error Analysis of a Model Order Reduction Framework for Financial Risk Analysis," Papers 2110.00774, arXiv.org.
  26. Jari Vepsäläinen & Antti Ritari & Antti Lajunen & Klaus Kivekäs & Kari Tammi, 2018. "Energy Uncertainty Analysis of Electric Buses," Energies, MDPI, vol. 11(12), pages 1-29, November.
  27. Hao, Wenrui & Lu, Zhenzhou & Wei, Pengfei, 2013. "Uncertainty importance measure for models with correlated normal variables," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 48-58.
  28. Chen, Xin & Molina-Cristóbal, Arturo & Guenov, Marin D. & Riaz, Atif, 2019. "Efficient method for variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 97-115.
  29. McFarland, John & DeCarlo, Erin, 2020. "A Monte Carlo framework for probabilistic analysis and variance decomposition with distribution parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  30. Matieyendou Lamboni, 2025. "Distributions of Outputs Given Subsets of Inputs and Dependent Generalized Sensitivity Indices," Mathematics, MDPI, vol. 13(5), pages 1-22, February.
  31. Xie, Xiangzhong & Schenkendorf, René & Krewer, Ulrike, 2019. "Efficient sensitivity analysis and interpretation of parameter correlations in chemical engineering," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 159-173.
  32. Mara, Thierry A. & Becker, William E., 2021. "Polynomial chaos expansion for sensitivity analysis of model output with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
  33. Kucherenko, S. & Klymenko, O.V. & Shah, N., 2017. "Sobol' indices for problems defined in non-rectangular domains," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 218-231.
  34. Lamboni, Matieyendou & Kucherenko, Sergei, 2021. "Multivariate sensitivity analysis and derivative-based global sensitivity measures with dependent variables," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
  35. Xiang Peng & Xiaoqing Xu & Jiquan Li & Shaofei Jiang, 2021. "A Sampling-Based Sensitivity Analysis Method Considering the Uncertainties of Input Variables and Their Distribution Parameters," Mathematics, MDPI, vol. 9(10), pages 1-18, May.
  36. 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.
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