Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models
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DOI: 10.1016/j.ress.2021.107815
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Cited by:
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- 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).
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- Barr, John & Rabitz, Herschel, 2023. "Kernel-based global sensitivity analysis obtained from a single data set," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Federica Gugole & Luc E Coffeng & Wouter Edeling & Benjamin Sanderse & Sake J de Vlas & Daan Crommelin, 2021. "Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-24, September.
- Blagojević, Nikola & Didier, Max & Stojadinović, Božidar, 2022. "Quantifying component importance for disaster resilience of communities with interdependent civil infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
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Keywords
Stochastic simulators; Surrogate modeling; Sensitivity analysis; Sobol’ indices; Generalized lambda distributions; Polynomial chaos expansions;All these keywords.
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